US20170162200A1 - Method of and system for providing adaptive respondent training in a speech recognition application - Google Patents
Method of and system for providing adaptive respondent training in a speech recognition application Download PDFInfo
- Publication number
- US20170162200A1 US20170162200A1 US15/438,067 US201715438067A US2017162200A1 US 20170162200 A1 US20170162200 A1 US 20170162200A1 US 201715438067 A US201715438067 A US 201715438067A US 2017162200 A1 US2017162200 A1 US 2017162200A1
- Authority
- US
- United States
- Prior art keywords
- respondent
- application
- speech recognition
- prompt
- telephonic
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Abandoned
Links
- 238000000034 method Methods 0.000 title claims description 27
- 238000012549 training Methods 0.000 title description 8
- 230000003044 adaptive effect Effects 0.000 title description 5
- 230000004044 response Effects 0.000 claims abstract description 23
- 230000008569 process Effects 0.000 claims description 12
- 230000008520 organization Effects 0.000 description 8
- 238000010586 diagram Methods 0.000 description 4
- 230000003993 interaction Effects 0.000 description 4
- 238000012360 testing method Methods 0.000 description 4
- 238000000605 extraction Methods 0.000 description 3
- 238000013528 artificial neural network Methods 0.000 description 2
- 230000008901 benefit Effects 0.000 description 2
- 230000001413 cellular effect Effects 0.000 description 2
- 238000007796 conventional method Methods 0.000 description 2
- 230000000694 effects Effects 0.000 description 2
- 230000006870 function Effects 0.000 description 2
- 230000000977 initiatory effect Effects 0.000 description 2
- 230000002452 interceptive effect Effects 0.000 description 2
- 238000012423 maintenance Methods 0.000 description 2
- 238000012552 review Methods 0.000 description 2
- 238000013459 approach Methods 0.000 description 1
- 230000015572 biosynthetic process Effects 0.000 description 1
- 238000006243 chemical reaction Methods 0.000 description 1
- 230000036541 health Effects 0.000 description 1
- 230000002401 inhibitory effect Effects 0.000 description 1
- 238000004519 manufacturing process Methods 0.000 description 1
- 238000012544 monitoring process Methods 0.000 description 1
- 238000003825 pressing Methods 0.000 description 1
- 238000012827 research and development Methods 0.000 description 1
- 238000012216 screening Methods 0.000 description 1
- 238000012795 verification Methods 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G10—MUSICAL INSTRUMENTS; ACOUSTICS
- G10L—SPEECH ANALYSIS TECHNIQUES OR SPEECH SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING TECHNIQUES; SPEECH OR AUDIO CODING OR DECODING
- G10L15/00—Speech recognition
- G10L15/22—Procedures used during a speech recognition process, e.g. man-machine dialogue
-
- G—PHYSICS
- G10—MUSICAL INSTRUMENTS; ACOUSTICS
- G10L—SPEECH ANALYSIS TECHNIQUES OR SPEECH SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING TECHNIQUES; SPEECH OR AUDIO CODING OR DECODING
- G10L15/00—Speech recognition
- G10L15/06—Creation of reference templates; Training of speech recognition systems, e.g. adaptation to the characteristics of the speaker's voice
- G10L15/063—Training
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04M—TELEPHONIC COMMUNICATION
- H04M3/00—Automatic or semi-automatic exchanges
- H04M3/42—Systems providing special services or facilities to subscribers
- H04M3/46—Arrangements for calling a number of substations in a predetermined sequence until an answer is obtained
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04M—TELEPHONIC COMMUNICATION
- H04M3/00—Automatic or semi-automatic exchanges
- H04M3/42—Systems providing special services or facilities to subscribers
- H04M3/487—Arrangements for providing information services, e.g. recorded voice services or time announcements
- H04M3/493—Interactive information services, e.g. directory enquiries ; Arrangements therefor, e.g. interactive voice response [IVR] systems or voice portals
- H04M3/4936—Speech interaction details
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04M—TELEPHONIC COMMUNICATION
- H04M3/00—Automatic or semi-automatic exchanges
- H04M3/42—Systems providing special services or facilities to subscribers
- H04M3/50—Centralised arrangements for answering calls; Centralised arrangements for recording messages for absent or busy subscribers ; Centralised arrangements for recording messages
- H04M3/51—Centralised call answering arrangements requiring operator intervention, e.g. call or contact centers for telemarketing
- H04M3/523—Centralised call answering arrangements requiring operator intervention, e.g. call or contact centers for telemarketing with call distribution or queueing
-
- G—PHYSICS
- G10—MUSICAL INSTRUMENTS; ACOUSTICS
- G10L—SPEECH ANALYSIS TECHNIQUES OR SPEECH SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING TECHNIQUES; SPEECH OR AUDIO CODING OR DECODING
- G10L21/00—Speech or voice signal processing techniques to produce another audible or non-audible signal, e.g. visual or tactile, in order to modify its quality or its intelligibility
-
- G—PHYSICS
- G10—MUSICAL INSTRUMENTS; ACOUSTICS
- G10L—SPEECH ANALYSIS TECHNIQUES OR SPEECH SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING TECHNIQUES; SPEECH OR AUDIO CODING OR DECODING
- G10L25/00—Speech or voice analysis techniques not restricted to a single one of groups G10L15/00 - G10L21/00
-
- G—PHYSICS
- G10—MUSICAL INSTRUMENTS; ACOUSTICS
- G10L—SPEECH ANALYSIS TECHNIQUES OR SPEECH SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING TECHNIQUES; SPEECH OR AUDIO CODING OR DECODING
- G10L25/00—Speech or voice analysis techniques not restricted to a single one of groups G10L15/00 - G10L21/00
- G10L25/03—Speech or voice analysis techniques not restricted to a single one of groups G10L15/00 - G10L21/00 characterised by the type of extracted parameters
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04M—TELEPHONIC COMMUNICATION
- H04M2201/00—Electronic components, circuits, software, systems or apparatus used in telephone systems
- H04M2201/40—Electronic components, circuits, software, systems or apparatus used in telephone systems using speech recognition
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04M—TELEPHONIC COMMUNICATION
- H04M2203/00—Aspects of automatic or semi-automatic exchanges
- H04M2203/20—Aspects of automatic or semi-automatic exchanges related to features of supplementary services
- H04M2203/2016—Call initiation by network rather than by subscriber
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04M—TELEPHONIC COMMUNICATION
- H04M2203/00—Aspects of automatic or semi-automatic exchanges
- H04M2203/35—Aspects of automatic or semi-automatic exchanges related to information services provided via a voice call
- H04M2203/355—Interactive dialogue design tools, features or methods
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04M—TELEPHONIC COMMUNICATION
- H04M3/00—Automatic or semi-automatic exchanges
- H04M3/38—Graded-service arrangements, i.e. some subscribers prevented from establishing certain connections
- H04M3/382—Graded-service arrangements, i.e. some subscribers prevented from establishing certain connections using authorisation codes or passwords
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04M—TELEPHONIC COMMUNICATION
- H04M3/00—Automatic or semi-automatic exchanges
- H04M3/42—Systems providing special services or facilities to subscribers
- H04M3/50—Centralised arrangements for answering calls; Centralised arrangements for recording messages for absent or busy subscribers ; Centralised arrangements for recording messages
- H04M3/51—Centralised call answering arrangements requiring operator intervention, e.g. call or contact centers for telemarketing
- H04M3/5158—Centralised call answering arrangements requiring operator intervention, e.g. call or contact centers for telemarketing in combination with automated outdialling systems
Definitions
- the present invention relates generally to a method of and system for providing adaptive respondent training in a speech recognition algorithm, and more particularly to a method of and system for determining the level of understanding and capability of a respondent to a telephonic speech recognition application, and both providing specific instructions to the respondent regarding the application and adapting the application to suit the capabilities of the respondent.
- a speech recognition system first converts an incoming analog voice signal into a digital signal. The second step is called feature extraction, wherein the system analyzes the digital signal to identify the acoustic properties of the digitized signal. Feature extraction generally breaks the voice down into its individual sound components.
- Conventional techniques for performing feature extraction include subband coding Fast Fourier Transforms and Linear Predictive Coding.
- the system determines where distinct acoustic regions occur.
- the goal of this step is to divide the acoustic signal into regions that will be identified as phonemes which can be converted to a textual format. In isolated word systems, this process is simplified, because there is a pause after each word. In continuous speech systems, however, this process is much more difficult, since there typically are no breaks between words in the acoustic stream. Accordingly, the system must be able not only to break the words themselves into distinct acoustic regions, but must also be able to separate consecutive words in the stream. It is in this step that conventional methods such as Hidden Markov modeling and neural networks are used.
- the final step involves comparing a specific acoustic region, as determined in the previous step, to a known set of templates in a database in order to determine the word or word portion represented by the acoustic signal region. If a match is found, the resulting textual word is output from the system. If one is not, the signal can either be dynamically manipulated in order to increase the chances of finding a match, or the data can be discarded and the system prompted to repeat the query to the respondent, if the associated answer cannot be determined due to the loss of the data.
- the present invention is directed to a method for adaptive training of a respondent to a telephonic speech recognition application.
- the method is used in connection with the speech recognition application to enable the administrator of the application to explain the function of the application, to train the respondent in how to effectively respond to the queries in the application and to adapt the application to the needs of the respondent, based on the initial responses given by the respondent.
- a method of conducting a telephonic speech recognition application including:
- the explanation may include at least one of a sample prompt and instructions on responding to the at least one prompt of the application.
- a system for conducting a telephonic speech recognition application including:
- a speech recognition device which, upon the telephonic contact being made, presents the respondent with at least one introductory prompt for the respondent to reply to; receives a spoken response from the respondent; and performs a speech recognition analysis on the spoken response to determine a capability of the respondent to complete the application;
- the speech recognition device determines that the respondent is capable of competing the application, the speech recognition device presents at least one application prompt to the respondent;
- the speech recognition system presents instructions on completing the application to the respondent.
- FIG. 1 is a schematic block diagram of the system for providing adaptive respondent training in accordance with the present invention
- FIG. 2 is a flow diagram of a method for providing adaptive respondent training in accordance with the present invention.
- FIGS. 3A-3C are flow diagrams showing an example of the instruction stage of the present invention.
- speech recognition ns can be an extremely efficient way to gather information from respondents, if the respondent is not able to respond to the prompts of the survey or does not understand the survey process or how to respond to certain types of queries, the process can be frustrating for respondent, thus inhibiting future interactions with the respondent, and the process can be costly and time consuming for the organization providing the service.
- the present invention includes a method and system for determining whether a respondent is capable of responding to the prompts in a telephonic speech recognition application and what extra explanations or instructions, with modified application functionality, might be required to assist the respondent in completing the application.
- the method is incorporated into the application, and responses to introductory prompts of the application direct the application to present prompts to the respondent that will enable the respondent to learn how to correctly complete the application.
- System 12 includes an automated telephone calling system 14 and a speech recognition system 16 .
- the automated telephone calling system 14 is a personal computer such as an IBM PC or IBM PC compatible system or an APPLE MacINTOSH system or a more advanced computer system such as an Alpha-based computer system available from Compaq Computer Corporation or SPARC Station computer system available from SUN Microsystems Corporation, although a main frame computer system can also be used.
- the components of the system will reside on the computer system, thus enabling the system to independently process data received from a respondent in the manner described below.
- the components may be included in different systems that have access to each other via a LAN or similar network.
- the automated telephone calling device 14 may reside on a server system which receives the audio response from a telephone 18 and transmits the response to the speech recognition device 16 .
- the automated telephone calling system 14 may also include a network interface that facilitates receipt of audio information by any of a variety of a networks, such as telephone networks, cellular telephone networks, the Web, Internet, local area networks (LANs), wide area networks (WANs), private networks, virtual private networks (VPNs), intranets, extranets, wireless networks, and the like, or some combination thereof
- a network such as telephone networks, cellular telephone networks, the Web, Internet, local area networks (LANs), wide area networks (WANs), private networks, virtual private networks (VPNs), intranets, extranets, wireless networks, and the like, or some combination thereof
- the system 10 may be accessible by any one or more of a variety of input devices capable of communicating audio information. Such devices may include, but are not limited to, a standard telephone or cellular telephone 18 .
- Automated telephone calling system 14 includes a database of persons to whom the system 12 is capable of initiating or receiving telephone calls, referred to hereinafter as the “target person”, a telephone number associated with each person and a recorded data file that includes the target person's name. Such automated telephone calling devices are known in the art. As is described below, the automated telephone calling system 14 is capable of initiating or receiving a telephone call to or from a target person and playing a prerecorded greeting prompt asking for the target person. The system 14 then interacts with speech recognition system 16 to analyze responses received from the person on telephone 18 .
- Speech recognition system 16 is an automated system on which a speech recognition application, including a series of acoustic outputs called prompts, which comprise queries about a particular topic, are programmed so that they can be presented to a respondent, preferably by means of a telephonic interaction between the querying party and the respondent.
- a speech recognition application may be any interactive application that collects, provides, and/or shares information.
- a speech application may be any of a group of interactive applications, including consumer service or survey applications; Web access applications; customer service applications; educational applications, including computer-based learning and lesson applications and testing applications; screening applications; consumer preference monitoring applications; compliance applications, including applications that generate notifications of compliance related activities, including notifications regarding product maintenance; test result applications, including applications that provide at least one of standardized tests results, consumer product test results, and maintenance results; and linking applications, including applications that link two or more of the above applications.
- each speech recognition application includes an application file programmed into the speech recognition system 16 .
- the series of queries that make up the application is designed to obtain specific information from the respondents to aid in customer or consumer service, education and research and development of particular products or services or other functions.
- a particular speech application could be designed to ask respondents specific queries about a particular product or service. The entity that issues the application may then use this information to further develop the particular product or service.
- An application may also be used to provide specific information to a particular person or department.
- FIG. 2 is a flow diagram which shows the method of adapting a speech recognition application and training a speech recognition application respondent in order to enable the respondent to effectively complete the application.
- the automatic calling system 14 initiates a call to the target person at telephone 18
- the target person initiates a telephone call to the system 12 based on information provided to the respondent by the organization providing the application.
- the system 12 initiates the application by providing an introduction to the respondent, stage 22 .
- the introduction generally identifies the host organization and informs the respondent of the purpose of the application.
- the system 12 provides a brief explanation of the application, including the fact that the respondent is speaking to a computer that is only capable of posing queries, recognizing certain of the respondent's responses
- the system then prompts the respondent to affirm that he or she understands how to interact with the system 12 .
- This prompt enables the system 12 to determine if the respondent is capable of interacting with an automated speech recognition system. Based on the response given, the system determines which step will be executed next. If the respondent replies quickly with a “yes” or some similar affirmation, the system may move on to the identification check, stage 26 , in which the respondent is asked to provide identification, typically in the form of a personal identification number (PIN), voice verification, or other method. While the use of a PIN is desirable in application surveys that address private matters concerning the respondent, the use of a PIN is not required in the present invention.
- PIN personal identification number
- the system 12 explains in greater detail how the system operates.
- the system prompts the respondent to answer “Hello” to a similar greeting offered by the system, as a training exercise for the respondent. If the respondent replies correctly, the system can repeat the explanation of the system and proceed to the identification stage 26 .
- the system can initiate several more attempts at, and approaches to trying to explain the process to the respondent, including attempting to determine whether the respondent is having difficulty hearing the application, in which the system 12 would be instructed to increase the volume of the prompts and/or to slow the speed at which the prompts are played by the system 12 . If the system is unable to teach the respondent how to respond to the application, the system enters an end call stage 25 , in which the respondent is thanked and optionally informed that they will be contacted by a human being, and the call is terminated.
- the respondent is asked for identification, which in one example may include a PIN. If the PIN is correctly input either by speaking the numbers or by pressing the number on the telephone keypad, the application moves to the instruction step 28 . If the respondent enters an incorrect PIN or does not know his or her PIN, the system enters an end call stage 25 , in which the respondent is thanked and optionally informed how they can obtain a proper PIN, and the call is terminated.
- identification stage 26 the respondent is asked for identification, which in one example may include a PIN. If the PIN is correctly input either by speaking the numbers or by pressing the number on the telephone keypad, the application moves to the instruction step 28 . If the respondent enters an incorrect PIN or does not know his or her PIN, the system enters an end call stage 25 , in which the respondent is thanked and optionally informed how they can obtain a proper PIN, and the call is terminated.
- the system After the identity of the respondent has been confirmed in step 26 , the system enters instruction stage 28 .
- instruction stage 28 the system 12 explains the purpose of the application and the benefits provided by the application.
- the system 12 explains the structure of the application and informs the respondent of what types of answers are necessary for the application to be successful.
- the system 12 can then provide a sample prompt to the respondent in order to prepare the respondent for what to expect during the actual application. If the survey includes a rating system, it is explained in this stage and the sample question can require an answer that uses the rating system.
- FIGS. 3A-3C An example of this process in shown in FIGS. 3A-3C , which include an example question and the options available, depending on the responses given. If, in this stage, the respondent is unable to answer the sample prompt satisfactorily, the system enters an end call stage 25 , in which the respondent is thanked and optionally informed that they will be contacted by a human being, and the call is terminated.
- stage 30 the system enters stage 30 , in which the prompts of the application are presented to the respondent.
- the system 12 can re-enter either or both of explanation stage 24 and instruction stage 28 to provide help for the respondent, as necessary.
- the system 12 when appropriate, can then return to survey stage 30 to complete the application.
- the system records each of the responses provided by the respondent for review at a later time.
- the system enters a “wrap up” stage 32 in which the respondent is informed that the survey is over and is thanked by the host organization for participating in the application.
- Application feedback stage 34 provides an opportunity for the respondent to have his or her comments regarding the application itself or regarding the speech recognition application system recorded for review by the host organization.
- the present invention enables the system 12 both to train the respondent in properly responding to the prompts of the associated application and to alter the course of the application based on responses to introductory and explanatory prompts. For example, if the respondent, from the beginning of the call, understands the application process and is capable of responding to the prompts, the explanation stage 24 and instruction stage 28 can be quickly navigated through, saving time and money for the host organization, since more respondents can be processed in a given period of time. On the other hand, if the respondent is having difficulty understanding or hearing the system 12 , the system is able to offer further explanations, training and sample prompts and, if the person is still not able to complete the survey, the system 12 is able to terminate the application.
Landscapes
- Engineering & Computer Science (AREA)
- Signal Processing (AREA)
- Human Computer Interaction (AREA)
- Computational Linguistics (AREA)
- Health & Medical Sciences (AREA)
- Audiology, Speech & Language Pathology (AREA)
- Physics & Mathematics (AREA)
- Acoustics & Sound (AREA)
- Multimedia (AREA)
- Business, Economics & Management (AREA)
- Marketing (AREA)
- Artificial Intelligence (AREA)
- Telephonic Communication Services (AREA)
- Electrically Operated Instructional Devices (AREA)
Abstract
Description
- This application is a continuation of U.S. patent application Ser. No. 13/052,412 filed Mar. 21, 2011, which is a continuation of U.S. patent application Ser. No. 11/273,528 filed Nov. 14, 2005, now, U.S. Pat. No. 7,933,775 , issued Apr. 26, 2011, which is a continuation of U.S. patent application Ser. No. 09/978,611 filed Oct. 16, 2001 which claims the benefit of priority from commonly owned U.S. Provisional Patent Application Ser. No. 60/241,757, filed Oct. 16, 2000, all of which applications are incorporated herein in their entirety.
- The present invention relates generally to a method of and system for providing adaptive respondent training in a speech recognition algorithm, and more particularly to a method of and system for determining the level of understanding and capability of a respondent to a telephonic speech recognition application, and both providing specific instructions to the respondent regarding the application and adapting the application to suit the capabilities of the respondent.
- In the new, connected economy, it has become increasingly important for companies or service providers to become more in tune with their clients and customers. Such contact can be facilitated with automated telephonic transaction systems, in which interactively-generated prompts are played in the context of a telephone transaction, and the replies of a human user are recognized by an automatic speech recognition system. The answers given by the respondent are processed by the system in order to convert the spoken words to meaning, which can then be utilized interactively, or stored in a database.
- In order for a computer system to recognize the words that are spoken and convert these words to text, the system must be programmed to phonetically break down the words and convert portions of the words to their textural equivalents. Such a conversion requires an understanding of the components of speech and the formation of the spoken word. The production of speech generates a complex series of rapidly changing acoustic pressure waveforms. These waveforms comprise the basic building blocks of speech, known as phonemes. Vowel and consonant sounds are made up of phonemes and have many different characteristics, depending on which components of human speech are used. The position of a phoneme in a word has a significant effect on the ultimate sound generated. A spoken word can have several meanings, depending on how it is said. Speech scientists have identified allophones as acoustic variants of phonemes and use them to more explicitly define how a particular word is formed.
- While there are several distinct methods for analyzing the spoken word and extracting the information necessary to enable the recognition system to convert the speech to word-strings, including Hidden Markov modeling and neural networks, these methods generally perform similar operations. The differences in these methods are typically in the manner in which the system determines how to break the phonetic signal into portions that define phonemes. Generally, a speech recognition system first converts an incoming analog voice signal into a digital signal. The second step is called feature extraction, wherein the system analyzes the digital signal to identify the acoustic properties of the digitized signal. Feature extraction generally breaks the voice down into its individual sound components. Conventional techniques for performing feature extraction include subband coding Fast Fourier Transforms and Linear Predictive Coding. Once the signal has been analyzed, the system then determines where distinct acoustic regions occur. The goal of this step is to divide the acoustic signal into regions that will be identified as phonemes which can be converted to a textual format. In isolated word systems, this process is simplified, because there is a pause after each word. In continuous speech systems, however, this process is much more difficult, since there typically are no breaks between words in the acoustic stream. Accordingly, the system must be able not only to break the words themselves into distinct acoustic regions, but must also be able to separate consecutive words in the stream. It is in this step that conventional methods such as Hidden Markov modeling and neural networks are used. The final step involves comparing a specific acoustic region, as determined in the previous step, to a known set of templates in a database in order to determine the word or word portion represented by the acoustic signal region. If a match is found, the resulting textual word is output from the system. If one is not, the signal can either be dynamically manipulated in order to increase the chances of finding a match, or the data can be discarded and the system prompted to repeat the query to the respondent, if the associated answer cannot be determined due to the loss of the data.
- In customer service applications, it is important for service providers to be able to obtain information from, or to provide information to, their customers. Oftentimes, service providers will need to contact customers via the telephone to obtain or provide the desired information. In order to reduce the costs associated with such information exchanges, many service providers utilize automated telephone calling devices to contact customers. While the automated telephone calling devices are extremely capable of converting spoken words into text phrases and thereby obtaining valuable information from respondents, in some cases, the respondents are not capable of providing adequate responses to the posed questions, or do not understand what is involved in an automated telephonic application. Prior art speech recognition applications are not able to identify that the respondent is having trouble with the application and then adjust the application accordingly. This results in wasted time and money for the company in charge of the survey and in frustration on the part of the respondent.
- The present invention is directed to a method for adaptive training of a respondent to a telephonic speech recognition application. The method is used in connection with the speech recognition application to enable the administrator of the application to explain the function of the application, to train the respondent in how to effectively respond to the queries in the application and to adapt the application to the needs of the respondent, based on the initial responses given by the respondent.
- According to one aspect of the invention, a method of conducting a telephonic speech recognition application is disclosed, including:
- A. making telephonic contact with a respondent;
- B. presenting the respondent with at least one introductory prompt to reply to;
- C. utilizing a speech recognition algorithm to process the audio responses given by the respondent to determine a level of capability of the respondent;
- D. based on the audio responses, presenting the respondent with one of:
-
- at least one prompt associated with an application; and
- an explanation of the operation of the speech recognition application.
- The explanation may include at least one of a sample prompt and instructions on responding to the at least one prompt of the application.
- According to another aspect of the invention, a system for conducting a telephonic speech recognition application is disclosed, including:
- an automated telephone device for making telephonic contact with a respondent; and
- a speech recognition device which, upon the telephonic contact being made, presents the respondent with at least one introductory prompt for the respondent to reply to; receives a spoken response from the respondent; and performs a speech recognition analysis on the spoken response to determine a capability of the respondent to complete the application;
- wherein, if the speech recognition device, based on the spoken response to the introductory prompt, determines that the respondent is capable of competing the application, the speech recognition device presents at least one application prompt to the respondent; and
- wherein, if the speech recognition device, based on the spoken response to the introductory prompt, determines that the respondent is not capable of completing the application, the speech recognition system presents instructions on completing the application to the respondent.
- The foregoing and other objects of this invention, the various features thereof, as well as the invention itself may be more fully understood from the following description when read together with the accompanying drawings in which:
-
FIG. 1 is a schematic block diagram of the system for providing adaptive respondent training in accordance with the present invention; -
FIG. 2 is a flow diagram of a method for providing adaptive respondent training in accordance with the present invention; and -
FIGS. 3A-3C are flow diagrams showing an example of the instruction stage of the present invention. - As set forth above, many customer-oriented organizations, including retail operations, service organizations, health care organizations, etc. rely on interactions with their customers in order to obtain valuable information that will enable the organizations to optimize their operations and to provide better service to the customers. Telephonic speech recognition applications, in which specific prompts about the organization's products or services, ‘enable the organizations to obtain information from customers’ in a manner which consumes very little time and which does not require repeat visits to the organization's location. For many organizations, these types of interactions are much less troublesome for customers who might have difficulties in traveling.
- While speech recognition ns can be an extremely efficient way to gather information from respondents, if the respondent is not able to respond to the prompts of the survey or does not understand the survey process or how to respond to certain types of queries, the process can be frustrating for respondent, thus inhibiting future interactions with the respondent, and the process can be costly and time consuming for the organization providing the service.
- The present invention includes a method and system for determining whether a respondent is capable of responding to the prompts in a telephonic speech recognition application and what extra explanations or instructions, with modified application functionality, might be required to assist the respondent in completing the application. The method is incorporated into the application, and responses to introductory prompts of the application direct the application to present prompts to the respondent that will enable the respondent to learn how to correctly complete the application.
- Referring now to
FIGS. 1-3 , a preferred embodiment of the present invention will be described.System 12,FIG. 1 , includes an automatedtelephone calling system 14 and aspeech recognition system 16. Preferably, the automatedtelephone calling system 14 is a personal computer such as an IBM PC or IBM PC compatible system or an APPLE MacINTOSH system or a more advanced computer system such as an Alpha-based computer system available from Compaq Computer Corporation or SPARC Station computer system available from SUN Microsystems Corporation, although a main frame computer system can also be used. In such a system, all of the components of the system will reside on the computer system, thus enabling the system to independently process data received from a respondent in the manner described below. Alternatively, the components may be included in different systems that have access to each other via a LAN or similar network. For example, the automatedtelephone calling device 14 may reside on a server system which receives the audio response from atelephone 18 and transmits the response to thespeech recognition device 16. - The automated
telephone calling system 14 may also include a network interface that facilitates receipt of audio information by any of a variety of a networks, such as telephone networks, cellular telephone networks, the Web, Internet, local area networks (LANs), wide area networks (WANs), private networks, virtual private networks (VPNs), intranets, extranets, wireless networks, and the like, or some combination thereof The system 10 may be accessible by any one or more of a variety of input devices capable of communicating audio information. Such devices may include, but are not limited to, a standard telephone orcellular telephone 18. Automatedtelephone calling system 14 includes a database of persons to whom thesystem 12 is capable of initiating or receiving telephone calls, referred to hereinafter as the “target person”, a telephone number associated with each person and a recorded data file that includes the target person's name. Such automated telephone calling devices are known in the art. As is described below, the automatedtelephone calling system 14 is capable of initiating or receiving a telephone call to or from a target person and playing a prerecorded greeting prompt asking for the target person. Thesystem 14 then interacts withspeech recognition system 16 to analyze responses received from the person ontelephone 18. -
Speech recognition system 16 is an automated system on which a speech recognition application, including a series of acoustic outputs called prompts, which comprise queries about a particular topic, are programmed so that they can be presented to a respondent, preferably by means of a telephonic interaction between the querying party and the respondent. However, a speech recognition application may be any interactive application that collects, provides, and/or shares information. As examples, in the present invention, a speech application may be any of a group of interactive applications, including consumer service or survey applications; Web access applications; customer service applications; educational applications, including computer-based learning and lesson applications and testing applications; screening applications; consumer preference monitoring applications; compliance applications, including applications that generate notifications of compliance related activities, including notifications regarding product maintenance; test result applications, including applications that provide at least one of standardized tests results, consumer product test results, and maintenance results; and linking applications, including applications that link two or more of the above applications. - In the preferred embodiment, each speech recognition application includes an application file programmed into the
speech recognition system 16. Preferably, the series of queries that make up the application is designed to obtain specific information from the respondents to aid in customer or consumer service, education and research and development of particular products or services or other functions. For example, a particular speech application could be designed to ask respondents specific queries about a particular product or service. The entity that issues the application may then use this information to further develop the particular product or service. An application may also be used to provide specific information to a particular person or department. -
FIG. 2 is a flow diagram which shows the method of adapting a speech recognition application and training a speech recognition application respondent in order to enable the respondent to effectively complete the application. First, either theautomatic calling system 14 initiates a call to the target person attelephone 18, or the target person initiates a telephone call to thesystem 12 based on information provided to the respondent by the organization providing the application. Thesystem 12 initiates the application by providing an introduction to the respondent, stage 22. The introduction generally identifies the host organization and informs the respondent of the purpose of the application. - In
stage 24, thesystem 12 provides a brief explanation of the application, including the fact that the respondent is speaking to a computer that is only capable of posing queries, recognizing certain of the respondent's responses The system then prompts the respondent to affirm that he or she understands how to interact with thesystem 12. This prompt enables thesystem 12 to determine if the respondent is capable of interacting with an automated speech recognition system. Based on the response given, the system determines which step will be executed next. If the respondent replies quickly with a “yes” or some similar affirmation, the system may move on to the identification check,stage 26, in which the respondent is asked to provide identification, typically in the form of a personal identification number (PIN), voice verification, or other method. While the use of a PIN is desirable in application surveys that address private matters concerning the respondent, the use of a PIN is not required in the present invention. - If the respondent answers “no” or does not respond to affirmation request in
stage 24, thesystem 12 explains in greater detail how the system operates. The system prompts the respondent to answer “Hello” to a similar greeting offered by the system, as a training exercise for the respondent. If the respondent replies correctly, the system can repeat the explanation of the system and proceed to theidentification stage 26. If the respondent is does not reply to the greeting request or replies with a reply that is not understood by thesystem 12, the system can initiate several more attempts at, and approaches to trying to explain the process to the respondent, including attempting to determine whether the respondent is having difficulty hearing the application, in which thesystem 12 would be instructed to increase the volume of the prompts and/or to slow the speed at which the prompts are played by thesystem 12. If the system is unable to teach the respondent how to respond to the application, the system enters anend call stage 25, in which the respondent is thanked and optionally informed that they will be contacted by a human being, and the call is terminated. - In
optional identification stage 26, the respondent is asked for identification, which in one example may include a PIN. If the PIN is correctly input either by speaking the numbers or by pressing the number on the telephone keypad, the application moves to theinstruction step 28. If the respondent enters an incorrect PIN or does not know his or her PIN, the system enters anend call stage 25, in which the respondent is thanked and optionally informed how they can obtain a proper PIN, and the call is terminated. - After the identity of the respondent has been confirmed in
step 26, the system entersinstruction stage 28. Ininstruction stage 28, thesystem 12 explains the purpose of the application and the benefits provided by the application. Thesystem 12 explains the structure of the application and informs the respondent of what types of answers are necessary for the application to be successful. Thesystem 12 can then provide a sample prompt to the respondent in order to prepare the respondent for what to expect during the actual application. If the survey includes a rating system, it is explained in this stage and the sample question can require an answer that uses the rating system. An example of this process in shown inFIGS. 3A-3C , which include an example question and the options available, depending on the responses given. If, in this stage, the respondent is unable to answer the sample prompt satisfactorily, the system enters anend call stage 25, in which the respondent is thanked and optionally informed that they will be contacted by a human being, and the call is terminated. - After
stage 28 has been completed satisfactorily, the system entersstage 30, in which the prompts of the application are presented to the respondent. At any point duringstage 30, if the respondent does not understand the process or becomes confused by the application, prompts or rating system, thesystem 12 can re-enter either or both ofexplanation stage 24 andinstruction stage 28 to provide help for the respondent, as necessary. Thesystem 12, when appropriate, can then return tosurvey stage 30 to complete the application. During the application, the system records each of the responses provided by the respondent for review at a later time. - At the completion of the application, the system enters a “wrap up”
stage 32 in which the respondent is informed that the survey is over and is thanked by the host organization for participating in the application.Application feedback stage 34 provides an opportunity for the respondent to have his or her comments regarding the application itself or regarding the speech recognition application system recorded for review by the host organization. - Accordingly, the present invention enables the
system 12 both to train the respondent in properly responding to the prompts of the associated application and to alter the course of the application based on responses to introductory and explanatory prompts. For example, if the respondent, from the beginning of the call, understands the application process and is capable of responding to the prompts, theexplanation stage 24 andinstruction stage 28 can be quickly navigated through, saving time and money for the host organization, since more respondents can be processed in a given period of time. On the other hand, if the respondent is having difficulty understanding or hearing thesystem 12, the system is able to offer further explanations, training and sample prompts and, if the person is still not able to complete the survey, thesystem 12 is able to terminate the application. - The invention may be embodied in other specific forms without departing from the spirit or essential characteristics thereof The present embodiments are therefore to be considered in respects as illustrative and not restrictive, the scope of the invention being indicated by the appended claims rather than by the foregoing description, and all changes which come within the meaning and range of the equivalency of the claims are therefore intended to be embraced therein.
Claims (1)
Priority Applications (2)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
US15/438,067 US20170162200A1 (en) | 2000-10-16 | 2017-02-21 | Method of and system for providing adaptive respondent training in a speech recognition application |
US15/911,965 US10522144B2 (en) | 2000-10-16 | 2018-03-05 | Method of and system for providing adaptive respondent training in a speech recognition application |
Applications Claiming Priority (5)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
US24175700P | 2000-10-16 | 2000-10-16 | |
US09/978,611 US20020059072A1 (en) | 2000-10-16 | 2001-10-16 | Method of and system for providing adaptive respondent training in a speech recognition application |
US11/273,528 US7933775B2 (en) | 2000-10-16 | 2005-11-14 | Method of and system for providing adaptive respondent training in a speech recognition application based upon the inherent response of the respondent |
US13/052,412 US9578169B2 (en) | 2000-10-16 | 2011-03-21 | Method of and system for providing adaptive respondent training in a speech recognition application |
US15/438,067 US20170162200A1 (en) | 2000-10-16 | 2017-02-21 | Method of and system for providing adaptive respondent training in a speech recognition application |
Related Parent Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
US13/052,412 Continuation US9578169B2 (en) | 2000-10-16 | 2011-03-21 | Method of and system for providing adaptive respondent training in a speech recognition application |
Related Child Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
US15/911,965 Continuation US10522144B2 (en) | 2000-10-16 | 2018-03-05 | Method of and system for providing adaptive respondent training in a speech recognition application |
Publications (1)
Publication Number | Publication Date |
---|---|
US20170162200A1 true US20170162200A1 (en) | 2017-06-08 |
Family
ID=22912057
Family Applications (5)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
US09/978,611 Abandoned US20020059072A1 (en) | 2000-10-16 | 2001-10-16 | Method of and system for providing adaptive respondent training in a speech recognition application |
US11/273,528 Expired - Fee Related US7933775B2 (en) | 2000-10-16 | 2005-11-14 | Method of and system for providing adaptive respondent training in a speech recognition application based upon the inherent response of the respondent |
US13/052,412 Expired - Lifetime US9578169B2 (en) | 2000-10-16 | 2011-03-21 | Method of and system for providing adaptive respondent training in a speech recognition application |
US15/438,067 Abandoned US20170162200A1 (en) | 2000-10-16 | 2017-02-21 | Method of and system for providing adaptive respondent training in a speech recognition application |
US15/911,965 Expired - Fee Related US10522144B2 (en) | 2000-10-16 | 2018-03-05 | Method of and system for providing adaptive respondent training in a speech recognition application |
Family Applications Before (3)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
US09/978,611 Abandoned US20020059072A1 (en) | 2000-10-16 | 2001-10-16 | Method of and system for providing adaptive respondent training in a speech recognition application |
US11/273,528 Expired - Fee Related US7933775B2 (en) | 2000-10-16 | 2005-11-14 | Method of and system for providing adaptive respondent training in a speech recognition application based upon the inherent response of the respondent |
US13/052,412 Expired - Lifetime US9578169B2 (en) | 2000-10-16 | 2011-03-21 | Method of and system for providing adaptive respondent training in a speech recognition application |
Family Applications After (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
US15/911,965 Expired - Fee Related US10522144B2 (en) | 2000-10-16 | 2018-03-05 | Method of and system for providing adaptive respondent training in a speech recognition application |
Country Status (5)
Country | Link |
---|---|
US (5) | US20020059072A1 (en) |
EP (1) | EP1332605A4 (en) |
AU (1) | AU2002213338A1 (en) |
CA (1) | CA2425844A1 (en) |
WO (1) | WO2002033946A1 (en) |
Cited By (1)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US10250749B1 (en) | 2017-11-22 | 2019-04-02 | Repnow Inc. | Automated telephone host system interaction |
Families Citing this family (16)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US20020059072A1 (en) * | 2000-10-16 | 2002-05-16 | Nasreen Quibria | Method of and system for providing adaptive respondent training in a speech recognition application |
US7609829B2 (en) * | 2001-07-03 | 2009-10-27 | Apptera, Inc. | Multi-platform capable inference engine and universal grammar language adapter for intelligent voice application execution |
US20050163136A1 (en) * | 2003-11-17 | 2005-07-28 | Leo Chiu | Multi-tenant self-service VXML portal |
US7697673B2 (en) * | 2003-11-17 | 2010-04-13 | Apptera Inc. | System for advertisement selection, placement and delivery within a multiple-tenant voice interaction service system |
GB2409087A (en) * | 2003-12-12 | 2005-06-15 | Ibm | Computer generated prompting |
US20070250311A1 (en) * | 2006-04-25 | 2007-10-25 | Glen Shires | Method and apparatus for automatic adjustment of play speed of audio data |
US8086455B2 (en) * | 2008-01-09 | 2011-12-27 | Microsoft Corporation | Model development authoring, generation and execution based on data and processor dependencies |
US9123338B1 (en) | 2012-06-01 | 2015-09-01 | Google Inc. | Background audio identification for speech disambiguation |
US9679568B1 (en) | 2012-06-01 | 2017-06-13 | Google Inc. | Training a dialog system using user feedback |
WO2014066855A1 (en) * | 2012-10-26 | 2014-05-01 | The Regents Of The University Of California | Methods of decoding speech from brain activity data and devices for practicing the same |
US20170213469A1 (en) * | 2016-01-25 | 2017-07-27 | Wespeke, Inc. | Digital media content extraction and natural language processing system |
WO2017192851A1 (en) * | 2016-05-04 | 2017-11-09 | Wespeke, Inc. | Automated generation and presentation of lessons via digital media content extraction |
US9843448B1 (en) * | 2017-06-07 | 2017-12-12 | Global Tel*Link Corporation | System and method for customizing inmate communication notification |
US10313521B2 (en) | 2017-08-15 | 2019-06-04 | Genesyc Telecommunications Laboratories, Inc | Automatic quality management of chat agents via chat bots |
US11080485B2 (en) * | 2018-02-24 | 2021-08-03 | Twenty Lane Media, LLC | Systems and methods for generating and recognizing jokes |
US20240169163A1 (en) * | 2022-11-23 | 2024-05-23 | Allstate Insurance Company | Systems and methods for user classification with respect to a chatbot |
Citations (62)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US4667065A (en) * | 1985-02-28 | 1987-05-19 | Bangerter Richard M | Apparatus and methods for electrical signal discrimination |
US4797910A (en) * | 1986-05-07 | 1989-01-10 | American Telphone And Telegraph Company, At&T Bell Laboratories | Automated operator assistance calls with voice processing |
US4941168A (en) * | 1988-09-21 | 1990-07-10 | U.S. Telecom International Inc. | System for the recognition of automated telephone answering devices and delivery of prerecorded messages to such devices |
US5027408A (en) * | 1987-04-09 | 1991-06-25 | Kroeker John P | Speech-recognition circuitry employing phoneme estimation |
US5163083A (en) * | 1990-10-12 | 1992-11-10 | At&T Bell Laboratories | Automation of telephone operator assistance calls |
US5168524A (en) * | 1989-08-17 | 1992-12-01 | Eliza Corporation | Speech-recognition circuitry employing nonlinear processing, speech element modeling and phoneme estimation |
US5208848A (en) * | 1991-08-26 | 1993-05-04 | At&T Bell Laboratories | Telecommunications call processing |
US5404400A (en) * | 1993-03-01 | 1995-04-04 | Dialogic Corporation | Outcalling apparatus |
US5420912A (en) * | 1993-02-27 | 1995-05-30 | Alcatel N.V. | Telephone having portable voice control module for playing back speech or performing a hands-free telephone function |
US5430792A (en) * | 1991-05-03 | 1995-07-04 | Electronic Information Systems, Inc. | Automated telephone calling system |
US5488652A (en) * | 1994-04-14 | 1996-01-30 | Northern Telecom Limited | Method and apparatus for training speech recognition algorithms for directory assistance applications |
US5499288A (en) * | 1990-05-15 | 1996-03-12 | Voice Control Systems, Inc. | Simultaneous voice recognition and verification to allow access to telephone network services |
US5566272A (en) * | 1993-10-27 | 1996-10-15 | Lucent Technologies Inc. | Automatic speech recognition (ASR) processing using confidence measures |
US5572583A (en) * | 1992-04-17 | 1996-11-05 | Bell Atlantic | Advanced intelligent network with intelligent peripherals interfaced to the integrated services control point |
US5594638A (en) * | 1993-12-29 | 1997-01-14 | First Opinion Corporation | Computerized medical diagnostic system including re-enter function and sensitivity factors |
US5649057A (en) * | 1989-05-17 | 1997-07-15 | Lucent Technologies Inc. | Speech recognition employing key word modeling and non-key word modeling |
US5652789A (en) * | 1994-09-30 | 1997-07-29 | Wildfire Communications, Inc. | Network based knowledgeable assistant |
US5719921A (en) * | 1996-02-29 | 1998-02-17 | Nynex Science & Technology | Methods and apparatus for activating telephone services in response to speech |
US5774357A (en) * | 1991-12-23 | 1998-06-30 | Hoffberg; Steven M. | Human factored interface incorporating adaptive pattern recognition based controller apparatus |
US5774525A (en) * | 1995-01-23 | 1998-06-30 | International Business Machines Corporation | Method and apparatus utilizing dynamic questioning to provide secure access control |
US5774858A (en) * | 1995-10-23 | 1998-06-30 | Taubkin; Vladimir L. | Speech analysis method of protecting a vehicle from unauthorized accessing and controlling |
US5787151A (en) * | 1995-05-18 | 1998-07-28 | Northern Telecom Limited | Telephony based delivery system of messages containing selected greetings |
US5797124A (en) * | 1996-05-30 | 1998-08-18 | Intervoice Limited Partnership | Voice-controlled voice mail having random-order message retrieval based on played spoken identifier list |
US5828731A (en) * | 1992-06-19 | 1998-10-27 | Inventions, Inc. | Method and apparatus for non-offensive termination of an outbound call and for detection of an answer of an outbound call by an answering machine |
US5867562A (en) * | 1996-04-17 | 1999-02-02 | Scherer; Gordon F. | Call processing system with call screening |
US5915001A (en) * | 1996-11-14 | 1999-06-22 | Vois Corporation | System and method for providing and using universally accessible voice and speech data files |
US5953393A (en) * | 1996-07-15 | 1999-09-14 | At&T Corp. | Personal telephone agent |
US5960063A (en) * | 1996-08-23 | 1999-09-28 | Kokusai Denshin Denwa Kabushiki Kaisha | Telephone speech recognition system |
US5982875A (en) * | 1996-01-31 | 1999-11-09 | Nokia Mobile Phones, Limited | Process and apparatus for interaction between a telephone and its user |
US5987414A (en) * | 1996-10-31 | 1999-11-16 | Nortel Networks Corporation | Method and apparatus for selecting a vocabulary sub-set from a speech recognition dictionary for use in real time automated directory assistance |
US6044347A (en) * | 1997-08-05 | 2000-03-28 | Lucent Technologies Inc. | Methods and apparatus object-oriented rule-based dialogue management |
US6073101A (en) * | 1996-02-02 | 2000-06-06 | International Business Machines Corporation | Text independent speaker recognition for transparent command ambiguity resolution and continuous access control |
US6075844A (en) * | 1997-11-18 | 2000-06-13 | At&T Corp. | Messaging system with remote messaging recording device where the message is routed based on the spoken name of the recipient |
US6081782A (en) * | 1993-12-29 | 2000-06-27 | Lucent Technologies Inc. | Voice command control and verification system |
US6094632A (en) * | 1997-01-29 | 2000-07-25 | Nec Corporation | Speaker recognition device |
US6101468A (en) * | 1992-11-13 | 2000-08-08 | Dragon Systems, Inc. | Apparatuses and methods for training and operating speech recognition systems |
US6154526A (en) * | 1996-12-04 | 2000-11-28 | Intellivoice Communications, Inc. | Data acquisition and error correcting speech recognition system |
US6157913A (en) * | 1996-11-25 | 2000-12-05 | Bernstein; Jared C. | Method and apparatus for estimating fitness to perform tasks based on linguistic and other aspects of spoken responses in constrained interactions |
US6269336B1 (en) * | 1998-07-24 | 2001-07-31 | Motorola, Inc. | Voice browser for interactive services and methods thereof |
US20010047261A1 (en) * | 2000-01-24 | 2001-11-29 | Peter Kassan | Partially automated interactive dialog |
US6327343B1 (en) * | 1998-01-16 | 2001-12-04 | International Business Machines Corporation | System and methods for automatic call and data transfer processing |
US6334103B1 (en) * | 1998-05-01 | 2001-12-25 | General Magic, Inc. | Voice user interface with personality |
US6374225B1 (en) * | 1998-10-09 | 2002-04-16 | Enounce, Incorporated | Method and apparatus to prepare listener-interest-filtered works |
US6385584B1 (en) * | 1999-04-30 | 2002-05-07 | Verizon Services Corp. | Providing automated voice responses with variable user prompting |
US20020059072A1 (en) * | 2000-10-16 | 2002-05-16 | Nasreen Quibria | Method of and system for providing adaptive respondent training in a speech recognition application |
US6405170B1 (en) * | 1998-09-22 | 2002-06-11 | Speechworks International, Inc. | Method and system of reviewing the behavior of an interactive speech recognition application |
US20020135618A1 (en) * | 2001-02-05 | 2002-09-26 | International Business Machines Corporation | System and method for multi-modal focus detection, referential ambiguity resolution and mood classification using multi-modal input |
US20020143546A1 (en) * | 2001-01-31 | 2002-10-03 | Layng Terrence V. | Teaching method and system |
US6560576B1 (en) * | 2000-04-25 | 2003-05-06 | Nuance Communications | Method and apparatus for providing active help to a user of a voice-enabled application |
US6604075B1 (en) * | 1999-05-20 | 2003-08-05 | Lucent Technologies Inc. | Web-based voice dialog interface |
US20030147518A1 (en) * | 1999-06-30 | 2003-08-07 | Nandakishore A. Albal | Methods and apparatus to deliver caller identification information |
US6606598B1 (en) * | 1998-09-22 | 2003-08-12 | Speechworks International, Inc. | Statistical computing and reporting for interactive speech applications |
US6606596B1 (en) * | 1999-09-13 | 2003-08-12 | Microstrategy, Incorporated | System and method for the creation and automatic deployment of personalized, dynamic and interactive voice services, including deployment through digital sound files |
US6678360B1 (en) * | 1985-07-10 | 2004-01-13 | Ronald A. Katz Technology Licensing, L.P. | Telephonic-interface statistical analysis system |
US6704410B1 (en) * | 1998-06-03 | 2004-03-09 | Avaya Inc. | System for automatically assigning skill levels to multiple skilled agents in call center agent assignment applications |
US6707889B1 (en) * | 1999-08-24 | 2004-03-16 | Microstrategy Incorporated | Multiple voice network access provider system and method |
US20040179659A1 (en) * | 2001-08-21 | 2004-09-16 | Byrne William J. | Dynamic interactive voice interface |
US6944592B1 (en) * | 1999-11-05 | 2005-09-13 | International Business Machines Corporation | Interactive voice response system |
US7137126B1 (en) * | 1998-10-02 | 2006-11-14 | International Business Machines Corporation | Conversational computing via conversational virtual machine |
US7143039B1 (en) * | 2000-08-11 | 2006-11-28 | Tellme Networks, Inc. | Providing menu and other services for an information processing system using a telephone or other audio interface |
US7197461B1 (en) * | 1999-09-13 | 2007-03-27 | Microstrategy, Incorporated | System and method for voice-enabled input for use in the creation and automatic deployment of personalized, dynamic, and interactive voice services |
US20080205601A1 (en) * | 2007-01-25 | 2008-08-28 | Eliza Corporation | Systems and Techniques for Producing Spoken Voice Prompts |
Family Cites Families (27)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US4625081A (en) * | 1982-11-30 | 1986-11-25 | Lotito Lawrence A | Automated telephone voice service system |
US4785408A (en) * | 1985-03-11 | 1988-11-15 | AT&T Information Systems Inc. American Telephone and Telegraph Company | Method and apparatus for generating computer-controlled interactive voice services |
US4866756A (en) * | 1986-04-16 | 1989-09-12 | Call It Co. | Interactive computerized communications systems with voice input and output |
US4964077A (en) * | 1987-10-06 | 1990-10-16 | International Business Machines Corporation | Method for automatically adjusting help information displayed in an online interactive system |
US5369685A (en) * | 1991-03-07 | 1994-11-29 | Sprint Communications Company L.P. | Voice-activated telephone directory and call placement system |
US5353331A (en) * | 1992-03-05 | 1994-10-04 | Bell Atlantic Network Services, Inc. | Personal communications service using wireline/wireless integration |
US5540589A (en) * | 1994-04-11 | 1996-07-30 | Mitsubishi Electric Information Technology Center | Audio interactive tutor |
US6375225B1 (en) | 1994-04-28 | 2002-04-23 | Promex Medical, Inc. | Combination sample dispenser and order form device |
US5715468A (en) * | 1994-09-30 | 1998-02-03 | Budzinski; Robert Lucius | Memory system for storing and retrieving experience and knowledge with natural language |
US6804332B1 (en) * | 1994-09-30 | 2004-10-12 | Wildfire Communications, Inc. | Network based knowledgeable assistant |
US5839107A (en) * | 1996-11-29 | 1998-11-17 | Northern Telecom Limited | Method and apparatus for automatically generating a speech recognition vocabulary from a white pages listing |
WO1998050907A1 (en) * | 1997-05-06 | 1998-11-12 | Speechworks International, Inc. | System and method for developing interactive speech applications |
EP0895396A3 (en) * | 1997-07-03 | 2004-01-14 | Texas Instruments Incorporated | Spoken dialogue system for information access |
CA2219008C (en) * | 1997-10-21 | 2002-11-19 | Bell Canada | A method and apparatus for improving the utility of speech recognition |
US6118866A (en) * | 1998-08-03 | 2000-09-12 | Geneys Telecommunications Laboratories, Inc. | Emergency call load management for call centers |
US6243684B1 (en) * | 1999-02-19 | 2001-06-05 | Usada, Inc. | Directory assistance system and method utilizing a speech recognition system and a live operator |
US6299452B1 (en) * | 1999-07-09 | 2001-10-09 | Cognitive Concepts, Inc. | Diagnostic system and method for phonological awareness, phonological processing, and reading skill testing |
US6978238B2 (en) * | 1999-07-12 | 2005-12-20 | Charles Schwab & Co., Inc. | Method and system for identifying a user by voice |
US6513009B1 (en) * | 1999-12-14 | 2003-01-28 | International Business Machines Corporation | Scalable low resource dialog manager |
GB0004097D0 (en) * | 2000-02-22 | 2000-04-12 | Ibm | Management of speech technology modules in an interactive voice response system |
US6757362B1 (en) * | 2000-03-06 | 2004-06-29 | Avaya Technology Corp. | Personal virtual assistant |
US20020005907A1 (en) | 2000-04-25 | 2002-01-17 | Alten Brett G. | Remote control unit with visual display device for cameras and video recorders |
GB0230125D0 (en) | 2002-12-24 | 2003-01-29 | Lg Philips Displays Netherland | Oxide cathode |
US8073699B2 (en) * | 2005-08-16 | 2011-12-06 | Nuance Communications, Inc. | Numeric weighting of error recovery prompts for transfer to a human agent from an automated speech response system |
US8261355B2 (en) | 2009-07-24 | 2012-09-04 | Cisco Technology, Inc. | Topology-aware attack mitigation |
GB201405235D0 (en) | 2014-03-24 | 2014-05-07 | Mcalpine & Co Ltd | Improved plumbing apparatus |
US10069500B2 (en) | 2016-07-14 | 2018-09-04 | Murata Manufacturing Co., Ltd. | Oven controlled MEMS oscillator |
-
2001
- 2001-10-16 US US09/978,611 patent/US20020059072A1/en not_active Abandoned
- 2001-10-16 AU AU2002213338A patent/AU2002213338A1/en not_active Abandoned
- 2001-10-16 WO PCT/US2001/032425 patent/WO2002033946A1/en not_active Application Discontinuation
- 2001-10-16 EP EP01981713A patent/EP1332605A4/en not_active Withdrawn
- 2001-10-16 CA CA002425844A patent/CA2425844A1/en not_active Abandoned
-
2005
- 2005-11-14 US US11/273,528 patent/US7933775B2/en not_active Expired - Fee Related
-
2011
- 2011-03-21 US US13/052,412 patent/US9578169B2/en not_active Expired - Lifetime
-
2017
- 2017-02-21 US US15/438,067 patent/US20170162200A1/en not_active Abandoned
-
2018
- 2018-03-05 US US15/911,965 patent/US10522144B2/en not_active Expired - Fee Related
Patent Citations (62)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US4667065A (en) * | 1985-02-28 | 1987-05-19 | Bangerter Richard M | Apparatus and methods for electrical signal discrimination |
US6678360B1 (en) * | 1985-07-10 | 2004-01-13 | Ronald A. Katz Technology Licensing, L.P. | Telephonic-interface statistical analysis system |
US4797910A (en) * | 1986-05-07 | 1989-01-10 | American Telphone And Telegraph Company, At&T Bell Laboratories | Automated operator assistance calls with voice processing |
US5027408A (en) * | 1987-04-09 | 1991-06-25 | Kroeker John P | Speech-recognition circuitry employing phoneme estimation |
US4941168A (en) * | 1988-09-21 | 1990-07-10 | U.S. Telecom International Inc. | System for the recognition of automated telephone answering devices and delivery of prerecorded messages to such devices |
US5649057A (en) * | 1989-05-17 | 1997-07-15 | Lucent Technologies Inc. | Speech recognition employing key word modeling and non-key word modeling |
US5168524A (en) * | 1989-08-17 | 1992-12-01 | Eliza Corporation | Speech-recognition circuitry employing nonlinear processing, speech element modeling and phoneme estimation |
US5499288A (en) * | 1990-05-15 | 1996-03-12 | Voice Control Systems, Inc. | Simultaneous voice recognition and verification to allow access to telephone network services |
US5163083A (en) * | 1990-10-12 | 1992-11-10 | At&T Bell Laboratories | Automation of telephone operator assistance calls |
US5430792A (en) * | 1991-05-03 | 1995-07-04 | Electronic Information Systems, Inc. | Automated telephone calling system |
US5208848A (en) * | 1991-08-26 | 1993-05-04 | At&T Bell Laboratories | Telecommunications call processing |
US5774357A (en) * | 1991-12-23 | 1998-06-30 | Hoffberg; Steven M. | Human factored interface incorporating adaptive pattern recognition based controller apparatus |
US5572583A (en) * | 1992-04-17 | 1996-11-05 | Bell Atlantic | Advanced intelligent network with intelligent peripherals interfaced to the integrated services control point |
US5828731A (en) * | 1992-06-19 | 1998-10-27 | Inventions, Inc. | Method and apparatus for non-offensive termination of an outbound call and for detection of an answer of an outbound call by an answering machine |
US6101468A (en) * | 1992-11-13 | 2000-08-08 | Dragon Systems, Inc. | Apparatuses and methods for training and operating speech recognition systems |
US5420912A (en) * | 1993-02-27 | 1995-05-30 | Alcatel N.V. | Telephone having portable voice control module for playing back speech or performing a hands-free telephone function |
US5404400A (en) * | 1993-03-01 | 1995-04-04 | Dialogic Corporation | Outcalling apparatus |
US5566272A (en) * | 1993-10-27 | 1996-10-15 | Lucent Technologies Inc. | Automatic speech recognition (ASR) processing using confidence measures |
US6081782A (en) * | 1993-12-29 | 2000-06-27 | Lucent Technologies Inc. | Voice command control and verification system |
US5594638A (en) * | 1993-12-29 | 1997-01-14 | First Opinion Corporation | Computerized medical diagnostic system including re-enter function and sensitivity factors |
US5488652A (en) * | 1994-04-14 | 1996-01-30 | Northern Telecom Limited | Method and apparatus for training speech recognition algorithms for directory assistance applications |
US5652789A (en) * | 1994-09-30 | 1997-07-29 | Wildfire Communications, Inc. | Network based knowledgeable assistant |
US5774525A (en) * | 1995-01-23 | 1998-06-30 | International Business Machines Corporation | Method and apparatus utilizing dynamic questioning to provide secure access control |
US5787151A (en) * | 1995-05-18 | 1998-07-28 | Northern Telecom Limited | Telephony based delivery system of messages containing selected greetings |
US5774858A (en) * | 1995-10-23 | 1998-06-30 | Taubkin; Vladimir L. | Speech analysis method of protecting a vehicle from unauthorized accessing and controlling |
US5982875A (en) * | 1996-01-31 | 1999-11-09 | Nokia Mobile Phones, Limited | Process and apparatus for interaction between a telephone and its user |
US6073101A (en) * | 1996-02-02 | 2000-06-06 | International Business Machines Corporation | Text independent speaker recognition for transparent command ambiguity resolution and continuous access control |
US5719921A (en) * | 1996-02-29 | 1998-02-17 | Nynex Science & Technology | Methods and apparatus for activating telephone services in response to speech |
US5867562A (en) * | 1996-04-17 | 1999-02-02 | Scherer; Gordon F. | Call processing system with call screening |
US5797124A (en) * | 1996-05-30 | 1998-08-18 | Intervoice Limited Partnership | Voice-controlled voice mail having random-order message retrieval based on played spoken identifier list |
US5953393A (en) * | 1996-07-15 | 1999-09-14 | At&T Corp. | Personal telephone agent |
US5960063A (en) * | 1996-08-23 | 1999-09-28 | Kokusai Denshin Denwa Kabushiki Kaisha | Telephone speech recognition system |
US5987414A (en) * | 1996-10-31 | 1999-11-16 | Nortel Networks Corporation | Method and apparatus for selecting a vocabulary sub-set from a speech recognition dictionary for use in real time automated directory assistance |
US5915001A (en) * | 1996-11-14 | 1999-06-22 | Vois Corporation | System and method for providing and using universally accessible voice and speech data files |
US6157913A (en) * | 1996-11-25 | 2000-12-05 | Bernstein; Jared C. | Method and apparatus for estimating fitness to perform tasks based on linguistic and other aspects of spoken responses in constrained interactions |
US6154526A (en) * | 1996-12-04 | 2000-11-28 | Intellivoice Communications, Inc. | Data acquisition and error correcting speech recognition system |
US6094632A (en) * | 1997-01-29 | 2000-07-25 | Nec Corporation | Speaker recognition device |
US6044347A (en) * | 1997-08-05 | 2000-03-28 | Lucent Technologies Inc. | Methods and apparatus object-oriented rule-based dialogue management |
US6075844A (en) * | 1997-11-18 | 2000-06-13 | At&T Corp. | Messaging system with remote messaging recording device where the message is routed based on the spoken name of the recipient |
US6327343B1 (en) * | 1998-01-16 | 2001-12-04 | International Business Machines Corporation | System and methods for automatic call and data transfer processing |
US6334103B1 (en) * | 1998-05-01 | 2001-12-25 | General Magic, Inc. | Voice user interface with personality |
US6704410B1 (en) * | 1998-06-03 | 2004-03-09 | Avaya Inc. | System for automatically assigning skill levels to multiple skilled agents in call center agent assignment applications |
US6269336B1 (en) * | 1998-07-24 | 2001-07-31 | Motorola, Inc. | Voice browser for interactive services and methods thereof |
US6405170B1 (en) * | 1998-09-22 | 2002-06-11 | Speechworks International, Inc. | Method and system of reviewing the behavior of an interactive speech recognition application |
US6606598B1 (en) * | 1998-09-22 | 2003-08-12 | Speechworks International, Inc. | Statistical computing and reporting for interactive speech applications |
US7137126B1 (en) * | 1998-10-02 | 2006-11-14 | International Business Machines Corporation | Conversational computing via conversational virtual machine |
US6374225B1 (en) * | 1998-10-09 | 2002-04-16 | Enounce, Incorporated | Method and apparatus to prepare listener-interest-filtered works |
US6385584B1 (en) * | 1999-04-30 | 2002-05-07 | Verizon Services Corp. | Providing automated voice responses with variable user prompting |
US6604075B1 (en) * | 1999-05-20 | 2003-08-05 | Lucent Technologies Inc. | Web-based voice dialog interface |
US20030147518A1 (en) * | 1999-06-30 | 2003-08-07 | Nandakishore A. Albal | Methods and apparatus to deliver caller identification information |
US6707889B1 (en) * | 1999-08-24 | 2004-03-16 | Microstrategy Incorporated | Multiple voice network access provider system and method |
US7197461B1 (en) * | 1999-09-13 | 2007-03-27 | Microstrategy, Incorporated | System and method for voice-enabled input for use in the creation and automatic deployment of personalized, dynamic, and interactive voice services |
US6606596B1 (en) * | 1999-09-13 | 2003-08-12 | Microstrategy, Incorporated | System and method for the creation and automatic deployment of personalized, dynamic and interactive voice services, including deployment through digital sound files |
US6944592B1 (en) * | 1999-11-05 | 2005-09-13 | International Business Machines Corporation | Interactive voice response system |
US20010047261A1 (en) * | 2000-01-24 | 2001-11-29 | Peter Kassan | Partially automated interactive dialog |
US6560576B1 (en) * | 2000-04-25 | 2003-05-06 | Nuance Communications | Method and apparatus for providing active help to a user of a voice-enabled application |
US7143039B1 (en) * | 2000-08-11 | 2006-11-28 | Tellme Networks, Inc. | Providing menu and other services for an information processing system using a telephone or other audio interface |
US20020059072A1 (en) * | 2000-10-16 | 2002-05-16 | Nasreen Quibria | Method of and system for providing adaptive respondent training in a speech recognition application |
US20020143546A1 (en) * | 2001-01-31 | 2002-10-03 | Layng Terrence V. | Teaching method and system |
US20020135618A1 (en) * | 2001-02-05 | 2002-09-26 | International Business Machines Corporation | System and method for multi-modal focus detection, referential ambiguity resolution and mood classification using multi-modal input |
US20040179659A1 (en) * | 2001-08-21 | 2004-09-16 | Byrne William J. | Dynamic interactive voice interface |
US20080205601A1 (en) * | 2007-01-25 | 2008-08-28 | Eliza Corporation | Systems and Techniques for Producing Spoken Voice Prompts |
Cited By (4)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US10250749B1 (en) | 2017-11-22 | 2019-04-02 | Repnow Inc. | Automated telephone host system interaction |
US10432790B2 (en) | 2017-11-22 | 2019-10-01 | Repnow Inc. | Automated telephone host system interaction |
US10477022B2 (en) | 2017-11-22 | 2019-11-12 | Repnow Inc. | Automated telephone host system interaction |
US11025778B2 (en) | 2017-11-22 | 2021-06-01 | Repnow Inc. | Automated telephone host system interaction |
Also Published As
Publication number | Publication date |
---|---|
US10522144B2 (en) | 2019-12-31 |
WO2002033946A1 (en) | 2002-04-25 |
EP1332605A1 (en) | 2003-08-06 |
AU2002213338A1 (en) | 2002-04-29 |
US20020059072A1 (en) | 2002-05-16 |
US20060122833A1 (en) | 2006-06-08 |
US7933775B2 (en) | 2011-04-26 |
US20110231190A1 (en) | 2011-09-22 |
US20180197541A1 (en) | 2018-07-12 |
US9578169B2 (en) | 2017-02-21 |
CA2425844A1 (en) | 2002-04-25 |
EP1332605A4 (en) | 2004-10-06 |
Similar Documents
Publication | Publication Date | Title |
---|---|---|
US10522144B2 (en) | Method of and system for providing adaptive respondent training in a speech recognition application | |
US10320982B2 (en) | Speech recognition method of and system for determining the status of an answered telephone during the course of an outbound telephone call | |
US10027804B2 (en) | System and method for providing hiring recommendations of agents within a call center | |
US8812314B2 (en) | Method of and system for improving accuracy in a speech recognition system | |
US10536582B2 (en) | Systems and methods for producing build calls | |
CN111241357A (en) | Dialogue training method, device, system and storage medium | |
CN109065052A (en) | A kind of speech robot people | |
Cole et al. | Experiments with a spoken dialogue system for taking the US census | |
CA2712853C (en) | Speech recognition method and system to determine the status of an outbound telephone call |
Legal Events
Date | Code | Title | Description |
---|---|---|---|
AS | Assignment |
Owner name: CITIBANK, N.A., AS COLLATERAL AGENT, NEW YORK Free format text: SECURITY AGREEMENT;ASSIGNOR:ELIZA CORPORATION;REEL/FRAME:044918/0119 Effective date: 20171219 |
|
STCB | Information on status: application discontinuation |
Free format text: ABANDONED -- FAILURE TO PAY ISSUE FEE |
|
AS | Assignment |
Owner name: ELIZA CORPORATION, MASSACHUSETTS Free format text: ASSIGNMENT OF ASSIGNORS INTEREST;ASSIGNORS:QUIBRIA, NASREEN;MERROW, LUCAS;BOULANOV, OLEG;AND OTHERS;REEL/FRAME:050374/0666 Effective date: 20060206 |
|
AS | Assignment |
Owner name: ELIZA CORPORATION, TEXAS Free format text: RELEASE BY SECURED PARTY;ASSIGNOR:CITIBANK, N.A.;REEL/FRAME:055812/0336 Effective date: 20210401 |