Abstract:
The present disclosure discloses a method for identifying an identity, device and a communication terminal. The method includes that: a voiceprint feature of a current call object and a mobile phone number of the current call object are extracted; the identity of the current call object is identified according to the voiceprint feature and the mobile phone number. The present disclosure solves the problem in the related art that it is difficult to effectively identify the identity of a call object, thus providing a method for effectively identifying the identity of a current call object and technically reducing the probability of phone fraud on a user.
Abstract:
A facility and method for analyzing and classifying calls without transcription via keyword spotting is disclosed. The facility uses a group of calls having known outcomes to generate one or more domain- or entity-specific grammars containing keywords and related information that are indicative of particular outcome. The facility monitors telephone calls by determining the domain or entity associated with the call, loading the appropriate grammar or grammars associated with the determined domain or entity, and tracking keywords contained in the loaded grammar or grammars that are spoken during the monitored call, along with additional information. The facility performs a statistical analysis on the tracked keywords and additional information to determine a classification for the monitored telephone call.
Abstract:
Techniques for ability enhancement are described. Some embodiments provide an ability enhancement facilitator system (“AEFS”) configured to enhance voice conferencing among multiple speakers. Some embodiments of the AEFS enhance voice conferencing by recording, translating and presenting voice conference history information based on speaker-related information, wherein the translation is based on language identification using multiple speech recognizers and GPS information. The AEFS receives data that represents utterances of multiple speakers who are engaging in a voice conference with one another. The AEFS then determines speaker-related information, such as by identifying a current speaker, locating an information item (e.g., an email message, document) associated with the speaker, or the like. The AEFS records conference history information (e.g., a transcript) based on the determined speaker-related information. The AEFS then informs a user of the conference history information, such as by presenting a transcript of the voice conference and/or related information items on a display of a conferencing device associated with the user.
Abstract:
A facility and method for analyzing and classifying calls without transcription via keyword spotting is disclosed. The facility uses a group of calls having known outcomes to generate one or more domain- or entity-specific grammars containing keywords and related information that are indicative of particular outcome. The facility monitors telephone calls by determining the domain or entity associated with the call, loading the appropriate grammar or grammars associated with the determined domain or entity, and tracking keywords contained in the loaded grammar or grammars that are spoken during the monitored call, along with additional information. The facility performs a statistical analysis on the tracked keywords and additional information to determine a classification for the monitored telephone call.
Abstract:
A method and apparatus of processing caller experiences is disclosed. One example method may include determining a call event type occurring during a call and assigning a weight to the call event type via a processing device. The method may also include calculating a caller experience metric value representing a caller's current call status responsive to determining the at least one call event type, the caller experience metric being a function of the current event type weight and a discounting variable that discounts a value of past events. The method may also provide comparing the caller experience metric to a predefined threshold value and determining whether to perform at least one of transferring the call to a live agent and switching from a current caller modality to a different caller modality.
Abstract:
Techniques for ability enhancement are described. Some embodiments provide an ability enhancement facilitator system (“AEFS”) configured to enhance voice conferencing among multiple speakers. Some embodiments of the AEFS enhance voice conferencing by recording and presenting voice conference history information based on speaker-related information. The AEFS receives data that represents utterances of multiple speakers who are engaging in a voice conference with one another. The AEFS then determines speaker-related information, such as by identifying a current speaker, locating an information item (e.g., an email message, document) associated with the speaker, or the like. The AEFS records conference history information (e.g., a transcript) based on the determined speaker-related information. The AEFS then informs a user of the conference history information, such as by presenting a transcript of the voice conference and/or related information items on a display of a conferencing device associated with the user.
Abstract:
A voice recognition server 200 has a voice reception unit 202 which receives a voice from a telephone equipment 100, a model storage unit 208 which stores at least one acoustic model and at least one language model used for converting the voice received by the voice reception unit 202, to character data, a number decision unit 204 which decides a current calling number and a second number of the telephone equipment 100, a model selection unit 206 which selects an acoustic model stored in the model storage unit 208, based on the current calling number and the second number, and which selects a language model stored in the model storage unit 208, based on the current calling number, and a voice recognition unit 210 which converts the voice received by the voice reception unit 202, to character data, based on the acoustic model and the language model selected by the model selection unit 206.
Abstract:
A method for spotting an interaction in which a target speaker associated with a current index or current interaction speaks, the method comprising: receiving an interaction and an index associated with the interaction, the index associated with additional data; receiving the current interaction or current index associated with the target speaker; obtaining current data associated with the current interaction or current index; filtering the index using the additional data, in accordance with the current data associated with the current interaction or current index, and obtaining a matching index; and comparing the current index or a representation of the current interaction with the matching index to obtain a target speaker index.
Abstract:
A voice recognition server 200 has a voice reception unit 202 which receives a voice from a telephone equipment 100, a model storage unit 208 which stores at least one acoustic model and at least one language model used for converting the voice received by the voice reception unit 202, to character data, a number decision unit 204 which decides a current calling number and a second number of the telephone equipment 100, a model selection unit 206 which selects an acoustic model stored in the model storage unit 208, based on the current calling number and the second number, and which selects a language model stored in the model storage unit 208, based on the current calling number, and a voice recognition unit 210 which converts the voice received by the voice reception unit 202, to character data, based on the acoustic model and the language model selected by the model selection unit 206.
Abstract:
Improved systems and methods are provided for transcribing audio files of voice mails sent over a unified messaging system. Customized grammars specific to a voice mail recipient are created and utilized to transcribe a received voice mail by comparing the audio file to commonly utilized words, names, acronyms, and phrases used by the recipient. Key elements are identified from the resulting text transcription to aid the recipient in processing received voice mails based on the significant content contained in the voice mail.