[go: nahoru, domu]

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 PDF

Info

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
Application number
US15/438,067
Inventor
Nasreen Quibria
Lucas Merrow
Oleg Boulanov
John P. Kroeker
Alexandra Drane
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Eliza Corp
Original Assignee
Eliza Corp
Priority date (The priority date 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 date listed.)
Filing date
Publication date
Application filed by Eliza Corp filed Critical Eliza Corp
Priority to US15/438,067 priority Critical patent/US20170162200A1/en
Publication of US20170162200A1 publication Critical patent/US20170162200A1/en
Assigned to CITIBANK, N.A., AS COLLATERAL AGENT reassignment CITIBANK, N.A., AS COLLATERAL AGENT SECURITY AGREEMENT Assignors: ELIZA CORPORATION
Priority to US15/911,965 priority patent/US10522144B2/en
Assigned to ELIZA CORPORATION reassignment ELIZA CORPORATION ASSIGNMENT OF ASSIGNORS INTEREST (SEE DOCUMENT FOR DETAILS). Assignors: BOULANOV, OLEG, DRANE, ALEXANDRA, KROEKER, JOHN P., MERROW, LUCAS, QUIBRIA, NASREEN
Assigned to ELIZA CORPORATION reassignment ELIZA CORPORATION RELEASE BY SECURED PARTY (SEE DOCUMENT FOR DETAILS). Assignors: CITIBANK, N.A.
Abandoned legal-status Critical Current

Links

Images

Classifications

    • GPHYSICS
    • G10MUSICAL INSTRUMENTS; ACOUSTICS
    • G10LSPEECH ANALYSIS TECHNIQUES OR SPEECH SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING TECHNIQUES; SPEECH OR AUDIO CODING OR DECODING
    • G10L15/00Speech recognition
    • G10L15/22Procedures used during a speech recognition process, e.g. man-machine dialogue
    • GPHYSICS
    • G10MUSICAL INSTRUMENTS; ACOUSTICS
    • G10LSPEECH ANALYSIS TECHNIQUES OR SPEECH SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING TECHNIQUES; SPEECH OR AUDIO CODING OR DECODING
    • G10L15/00Speech recognition
    • G10L15/06Creation of reference templates; Training of speech recognition systems, e.g. adaptation to the characteristics of the speaker's voice
    • G10L15/063Training
    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04MTELEPHONIC COMMUNICATION
    • H04M3/00Automatic or semi-automatic exchanges
    • H04M3/42Systems providing special services or facilities to subscribers
    • H04M3/46Arrangements for calling a number of substations in a predetermined sequence until an answer is obtained
    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04MTELEPHONIC COMMUNICATION
    • H04M3/00Automatic or semi-automatic exchanges
    • H04M3/42Systems providing special services or facilities to subscribers
    • H04M3/487Arrangements for providing information services, e.g. recorded voice services or time announcements
    • H04M3/493Interactive information services, e.g. directory enquiries ; Arrangements therefor, e.g. interactive voice response [IVR] systems or voice portals
    • H04M3/4936Speech interaction details
    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04MTELEPHONIC COMMUNICATION
    • H04M3/00Automatic or semi-automatic exchanges
    • H04M3/42Systems providing special services or facilities to subscribers
    • H04M3/50Centralised arrangements for answering calls; Centralised arrangements for recording messages for absent or busy subscribers ; Centralised arrangements for recording messages
    • H04M3/51Centralised call answering arrangements requiring operator intervention, e.g. call or contact centers for telemarketing
    • H04M3/523Centralised call answering arrangements requiring operator intervention, e.g. call or contact centers for telemarketing with call distribution or queueing
    • GPHYSICS
    • G10MUSICAL INSTRUMENTS; ACOUSTICS
    • G10LSPEECH ANALYSIS TECHNIQUES OR SPEECH SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING TECHNIQUES; SPEECH OR AUDIO CODING OR DECODING
    • G10L21/00Speech 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
    • GPHYSICS
    • G10MUSICAL INSTRUMENTS; ACOUSTICS
    • G10LSPEECH ANALYSIS TECHNIQUES OR SPEECH SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING TECHNIQUES; SPEECH OR AUDIO CODING OR DECODING
    • G10L25/00Speech or voice analysis techniques not restricted to a single one of groups G10L15/00 - G10L21/00
    • GPHYSICS
    • G10MUSICAL INSTRUMENTS; ACOUSTICS
    • G10LSPEECH ANALYSIS TECHNIQUES OR SPEECH SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING TECHNIQUES; SPEECH OR AUDIO CODING OR DECODING
    • G10L25/00Speech or voice analysis techniques not restricted to a single one of groups G10L15/00 - G10L21/00
    • G10L25/03Speech or voice analysis techniques not restricted to a single one of groups G10L15/00 - G10L21/00 characterised by the type of extracted parameters
    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04MTELEPHONIC COMMUNICATION
    • H04M2201/00Electronic components, circuits, software, systems or apparatus used in telephone systems
    • H04M2201/40Electronic components, circuits, software, systems or apparatus used in telephone systems using speech recognition
    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04MTELEPHONIC COMMUNICATION
    • H04M2203/00Aspects of automatic or semi-automatic exchanges
    • H04M2203/20Aspects of automatic or semi-automatic exchanges related to features of supplementary services
    • H04M2203/2016Call initiation by network rather than by subscriber
    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04MTELEPHONIC COMMUNICATION
    • H04M2203/00Aspects of automatic or semi-automatic exchanges
    • H04M2203/35Aspects of automatic or semi-automatic exchanges related to information services provided via a voice call
    • H04M2203/355Interactive dialogue design tools, features or methods
    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04MTELEPHONIC COMMUNICATION
    • H04M3/00Automatic or semi-automatic exchanges
    • H04M3/38Graded-service arrangements, i.e. some subscribers prevented from establishing certain connections
    • H04M3/382Graded-service arrangements, i.e. some subscribers prevented from establishing certain connections using authorisation codes or passwords
    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04MTELEPHONIC COMMUNICATION
    • H04M3/00Automatic or semi-automatic exchanges
    • H04M3/42Systems providing special services or facilities to subscribers
    • H04M3/50Centralised arrangements for answering calls; Centralised arrangements for recording messages for absent or busy subscribers ; Centralised arrangements for recording messages
    • H04M3/51Centralised call answering arrangements requiring operator intervention, e.g. call or contact centers for telemarketing
    • H04M3/5158Centralised 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

A system for conducting a telephonic speech recognition application includes 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. 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. 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.

Description

    Cross References To Related Applications
  • 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.
  • FIELD OF THE INVENTION
  • 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.
  • BACKGROUND OF THE INVENTION
  • 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.
  • SUMMARY OF THE INVENTION
  • 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.
  • BRIEF DESCRIPTION OF THE DRAWINGS
  • 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.
  • DETAILED DESCRIPTION
  • 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 automated telephone calling system 14 and a speech recognition system 16. Preferably, 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. 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 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 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. 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 the automatic calling system 14 initiates a call to the target person at telephone 18, or 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.
  • In stage 24, 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.
  • If the respondent answers “no” or does not respond to affirmation request in stage 24, 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. If the respondent is does not reply to the greeting request or replies with a reply that is not understood by the system 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 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.
  • 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 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.
  • After the identity of the respondent has been confirmed in step 26, the system enters instruction stage 28. In 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. 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.
  • After stage 28 has been completed satisfactorily, the system enters stage 30, in which the prompts of the application are presented to the respondent. At any point during stage 30, if the respondent does not understand the process or becomes confused by the application, prompts or rating system, 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. 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, 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.
  • 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)

1. A method of conducting a telephonic speech recognition application comprising:
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 said audio responses, presenting the respondent with one of:
at least one prompt associated with an application; and
an explanation of the operation of said speech recognition application.
US15/438,067 2000-10-16 2017-02-21 Method of and system for providing adaptive respondent training in a speech recognition application Abandoned US20170162200A1 (en)

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)

* Cited by examiner, † Cited by third party
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)

* Cited by examiner, † Cited by third party
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)

* Cited by examiner, † Cited by third party
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)

* Cited by examiner, † Cited by third party
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

Patent Citations (62)

* Cited by examiner, † Cited by third party
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)

* Cited by examiner, † Cited by third party
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