The present invention discloses a method for speaker recognition and an apparatus for speaker recognition. The method for speaker recognition comprises: extracting, from a speaker-to-be-recognized corpus, voice characteristics of a speaker to be recognized: obtaining a speaker-to-be-recognized model based on the extracted voice characteristics of the speaker to be recognized, a universal background model UBM reflecting distribution of the voice characteristics in a characteristic space, a gradient universal speaker model GUSM reflecting statistic values of changes of the distribution of the voice characterizes in the characteristic space and a total change matrix reflecting environmental changes; and comparing the speaker-to-be-recognized model with known speaker models, to determine whether or not the speaker to be recognized is one of known speakers.

The present invention discloses a method for speaker recognition and an apparatus for speaker recognition. The method for speaker recognition comprises: extracting, from a speaker-to-be-recognized corpus, voice characteristics of a speaker to be recognized: obtaining a speaker-to-be-recognized model based on the extracted voice characteristics of the speaker to be recognized, a universal background model UBM reflecting distribution of the voice characteristics in a characteristic space, a gradient universal speaker model GUSM reflecting statistic values of changes of the distribution of the voice characterizes in the characteristic space and a total change matrix reflecting environmental changes; and comparing the speaker-to-be-recognized model with known speaker models, to determine whether or not the speaker to be recognized is one of known speakers.

A method for estimating the reliability of a result of a speaker recognition system concerning a testing audio and a speaker model, which is based on one, two, three or more model audios, the method using a Bayesian Network to estimate whether the result is reliable. In estimating the reliability of the result of the speaker recognition system one, two, three, four or more than four quality measures of the testing audio and one, two, three, four or more than four quality measures of the model audio(s) are used.

A method for estimating the reliability of a result of a speaker recognition system concerning a testing audio and a speaker model, which is based on one, two, three or more model audios, the method using a Bayesian Network to estimate whether the result is reliable. In estimating the reliability of the result of the speaker recognition system one, two, three, four or more than four quality measures of the testing audio and one, two, three, four or more than four quality measures of the model audio(s) are used.

An interactive response system mixes HSR subsystems with ASR subsystems to facilitate overall capability of voice user interfaces. The system permits imperfect ASR subsystems to nonetheless relieve burden on HSR subsystems. An ASR proxy is used to implement an IVR system, and the proxy dynamically determines how many ASR and HSR subsystems are to perform recognition for any particular utterance, based on factors such as confidence thresholds of the ASRs and availability of human resources for HSRs. In some embodiments, the ASR proxy dynamically selects one or more recognizers based at least in part on the identified grammar and the time length of the utterance.

An interactive response system mixes HSR subsystems with ASR subsystems to facilitate overall capability of voice user interfaces. The system permits imperfect ASR subsystems to nonetheless relieve burden on HSR subsystems. An ASR proxy is used to implement an IVR system, and the proxy dynamically determines how many ASR and HSR subsystems are to perform recognition for any particular utterance, based on factors such as confidence thresholds of the ASRs and availability of human resources for HSRs. In some embodiments, the ASR proxy dynamically selects one or more recognizers based at least in part on the identified grammar and the time length of the utterance.

Disclosed are a method and an apparatus for identifying animal species by using audiovisual information. A method for identifying animal species, according to one embodiment of the present invention, may include: a step of receiving an input signal for an object to be identified; a step of processing image information and acoustic information based on the input signal, wherein a processing result of the image information and a processing result of the acoustic information are represented by class-specific scores; a step of determining whether the image information processing result and the acoustic information processing result corresponding to the input signal exist; and a final result derivation step of fusing the image information processing result and the acoustic information processing result according to the determination result and classifying the object to be identified as a certain animal species by using the fused processing result.

A device may receive a command associated with identifying a merchant for a virtual card swap procedure wherein the virtual card swap procedure is to replace a credit card of a user with a virtual card corresponding to the credit card. The device may identify the merchant for the virtual card swap procedure based on the command. The device may obtain the virtual card for the user. The device may determine a virtual card swap procedure template for the merchant. The device may perform the virtual card swap procedure based on the virtual card swap procedure template.

An electronic device may include: a memory; a sound sensor; and a processor, wherein the processor is configured to: receive, from the sound sensor, sound data including a first piece of data corresponding to a first frequency band and a second piece of data corresponding to a second frequency band different from the first frequency band; receive voice data related to a voice of a registered user from the memory; perform voice identification by comparing the first piece of data and the second piece of data with the voice data related to the voice of the registered user; and determine an output based on a result of the voice identification.

One embodiment provides a method, including: detecting, using an audio capture device associated with an information handling device, audible input; determining, using a processor, whether the audible input is associated with an authorized user; and performing, responsive to determining that the audible input is not associated with the authorized user, a silencing action associated with the audio capture device. Other aspects are described and claimed.