Abstract:
Transparent voice registration of a party is provided in order to provide voice verification for communications with a service center. Verbal communication spoken by a party during interaction between the party and an agent of the service center is captured. A voice model associated with the captured communication is created and stored in order to provide voice verification during a subsequent call to the service center. When a requester contacts the service center, a comparison of the voice of the requester and a voice model of the person that the requester claims to be is performed, in order to verify the identity of the requester. Additionally, a voice model associated with a party is automatically updated after a subsequent communication between the party and the service center.
Abstract:
Disclosed herein are systems, methods, and computer-readable storage media for improving automatic speech recognition performance. A system practicing the method identifies idle speech recognition resources and establishes a supplemental speech recognizer on the idle resources based on overall speech recognition demand. The supplemental speech recognizer can differ from a main speech recognizer, and, along with the main speech recognizer, can be associated with a particular speaker. The system performs speech recognition on speech received from the particular speaker in parallel with the main speech recognizer and the supplemental speech recognizer and combines results from the main and supplemental speech recognizer. The system recognizes the received speech based on the combined results. The system can use beam adjustment in place of or in combination with a supplemental speech recognizer. A scheduling algorithm can tailor a particular combination of speech recognition resources and release the supplemental speech recognizer based on increased demand.
Abstract:
Disclosed are systems, methods, and computer readable media for performing speech recognition. The method embodiment comprises selecting a codebook from a plurality of codebooks with a minimal acoustic distance to a received speech sample, the plurality of codebooks generated by a process of (a) computing a vocal tract length for a each of a plurality of speakers, (b) for each of the plurality of speakers, clustering speech vectors, and (c) creating a codebook for each speaker, the codebook containing entries for the respective speaker's vocal tract length, speech vectors, and an optional vector weight for each speech vector, (2) applying the respective vocal tract length associated with the selected codebook to normalize the received speech sample for use in speech recognition, and (3) recognizing the received speech sample based on the respective vocal tract length associated with the selected codebook.
Abstract:
Disclosed herein are systems, methods, and computer readable-media for creating a speech search platform for coupons. The method includes receiving coupons from vendors, generating indexing information about the received coupons for use with speech searches, integrating the received coupons and respective indexing information into a database accessible through a Representational State Transfer (REST) Application Programming Interface (API) as part of a speech search platform for coupons, receiving from a user a natural language query through the speech search platform for coupons, identifying coupons in the database which match the natural language query based on location and a user profile, and transmitting the identified coupons to the user. The method can further include modifying the REST API to include coupon-specific parameters. Identified coupons can be transmitted to the consumer by notifying a coupon issuer that the user is entitled to a discount.
Abstract:
Disclosed herein are systems, methods and non-transitory computer-readable media for performing speech recognition across different applications or environments without model customization or prior knowledge of the domain of the received speech. The disclosure includes recognizing received speech with a collection of domain-specific speech recognizers, determining a speech recognition confidence for each of the speech recognition outputs, selecting speech recognition candidates based on a respective speech recognition confidence for each speech recognition output, and combining selected speech recognition candidates to generate text based on the combination.
Abstract:
A method includes registering a voice of a party in order to provide voice verification for communications with an entity. A call is received from a party at a voice response system. The party is prompted for information and verbal communication spoken by the party is captured. A voice model associated with the party is created by processing the captured verbal communication spoken by the party and is stored. The identity of the party is verified and a previously stored voice model of the party, registered during a previous call from the party, is updated. The creation of the voice model is imperceptible to the party.
Abstract:
A method, a system and a machine-readable medium are provided for an on demand translation service. A translation module including at least one language pair module for translating a source language to a target language may be made available for use by a subscriber. The subscriber may be charged a fee for use of the requested on demand translation service or may be provided use of the on demand translation service for free in exchange for displaying commercial messages to the subscriber. A video signal may be received including information in the source language, which may be obtained as text from the video signal and may be translated from the source language to the target language by use of the translation module. Translated information, based on the translated text, may be added into the received video signal. The video signal including the translated information in the target language may be sent to a display device.
Abstract:
Disclosed are systems, methods, and computer readable media for identifying an acoustic environment of a caller. The method embodiment comprises analyzing acoustic features of a received audio signal from a caller, receiving meta-data information, classifying a background environment of the caller based on the analyzed acoustic features and the meta-data, selecting an acoustic model matched to the classified background environment from a plurality of acoustic models, and performing speech recognition as the received audio signal using the selected acoustic model.