Abstract: A noise-environment storing unit stores therein a compensation vector for compensating a feature vector of a speech. A feature-vector extracting unit extracts the feature vector of the speech in each of a plurality of frames. A noise-environment-series estimating unit estimates a noise-environment series based on a feature-vector series and a degree of similarity. A calculating unit obtains a compensation vector corresponding to each noise environment in estimated noise-environment series based on the compensation vector present in the noise-environment storing unit. A compensating unit compensates the extracted feature vector of the speech based on obtained compensation vector.

Abstract: A computer-implemented method for providing content includes extracting preconfigured content from an application; selecting, from second content associated with the application, a plurality of portions of the second content using the extracted preconfigured content; ranking the plurality of portions based at least in part on the preconfigured content; and associating a reference with the preconfigured content in the application such that the reference is displayed with the application, the reference providing user navigation to at least one of the plurality of portions selected based on the ranking.

Abstract: A computer-implemented method for providing content includes extracting preconfigured content from an application; selecting, from second content associated with the application, a plurality of portions of the second content using the extracted preconfigured content; ranking the plurality of portions based at least in part on the preconfigured content; and associating a reference with the preconfigured content in the application such that the reference is displayed with the application, the reference providing user navigation to at least one of the plurality of portions selected based on the ranking.

Abstract: A system and method for generating on-demand voiceprints are presented wherein voiceprints are created on the fly using voice recordings and associated metadata specified by an application. The application requests a voiceprint and specifies a description of the data necessary to generate the voiceprint, including the appropriate voice recordings, the requisite verification engine and other parameters that should be utilized to generate the voiceprint. The specified voice recordings are accessed from storage and a voiceprint is produced using the designated speech engine and application-specified parameters.

Abstract: A system and method are provided for improving the accuracy of speaker authentication by combining the results of multiple verification sources using statistical modeling. A statistical classifier is built on top of the underlying verification sources. The classifier combines the multiple verification inputs with associated models of the respective verification technologies underlying the verification inputs. The classifier functions to classify a claimant as a true speaker or impostor based upon the verification inputs, the model or models and, potentially, additional information related to the context in which the classifier is being used.

Abstract: A speech recognition device includes an extracting unit that analyzes an input signal and extracts a feature to be used for speech recognition from the input signal; a storing unit configured to store therein an acoustic model that is a stochastic model for estimating what type of a phoneme is included in the feature; a speech-recognition unit that performs speech recognition on the input signal based on the feature and determines a word having maximum likelihood from the acoustic model; and an optimizing unit that dynamically self-optimizes parameters of the feature and the acoustic model depending on at least one of the input signal and a state of the speech recognition performed by the speech-recognition unit.

Abstract: A feature extracting unit extracts a feature vector of an input speech. A similarity calculating unit calculates degrees of similarity for each of a plurality of noise environments, based on the feature vector. A compensation-vector calculating unit acquires a first compensation vector from a storing unit, calculates a second compensation vector based on the first compensation vector, and calculates a third compensation vector by weighting and summing the second compensation vector with the degree of similarity as weights. A compensating unit compensates the feature vector based on the third compensation vector.

Abstract: A noise-environment storing unit stores therein a compensation vector for compensating a feature vector of a speech. A feature-vector extracting unit extracts the feature vector of the speech in each of a plurality of frames. A noise-environment-series estimating unit estimates a noise-environment series based on a feature-vector series and a degree of similarity. A calculating unit obtains a compensation vector corresponding to each noise environment in estimated noise-environment series based on the compensation vector present in the noise-environment storing unit. A compensating unit compensates the extracted feature vector of the speech based on obtained compensation vector.

Abstract: A system and method for generating on-demand voiceprints are presented wherein voiceprints are created on the fly using voice recordings and associated metadata specified by an application. The application requests a voiceprint and specifies a description of the data necessary to generate the voiceprint, including the appropriate voice recordings, the requisite verification engine and other parameters that should be utilized to generate the voiceprint. The specified voice recordings are accessed from storage and a voiceprint is produced using the designated speech engine and application-specified parameters.

Abstract: A system and method are provided for improving the accuracy of speaker authentication by combining the results of multiple verification sources using statistical modeling. A statistical classifier is built on top of the underlying verification sources. The classifier combines the multiple verification inputs with associated models of the respective verification technologies underlying the verification inputs. The classifier functions to classify a claimant as a true speaker or impostor based upon the verification inputs, the model or models and, potentially, additional information related to the context in which the classifier is being used.

Abstract: A voice processing and verification system accounts for variations dependent upon telephony equipment differences. Models are developed for the various types of telephony equipment from many users speaking on each of the types of equipment. A transformation algorithm is determined for making a transformation between each of the various types of equipment to each of the others. In other words, a model is formed for carbon button telephony equipment from many users. Similarly, a model is formed for electret telephony equipment from many users, and for cellular telephony equipment from many users. During an enrollment, a user speaks to the system. The system forms and stores a model of the user's speech. The type of telephony equipment used in the original enrollment session is also detected and stored along with the enrollment voice model. The system determines the types of telephony equipment being used based upon the spectrum of sound it receives.