A speaker identifier 130 identifies a speaker determining a most likely one of the speaker models for an utterance received from the speaker.
The speaker associated with the most likely speaker model is identified as the speaker of the test utterance.
A speaker recognition system (1) includes a speaker model registration device (10) which registers a speaker model for speaker recognition in the speaker recognition system.
When a speaker who has made an utterance is judged to be a registered speaker corresponding to an adaptive speaker model, the adaptive speaker model is updated.
A method and apparatus for spotting a target speaker within a call interaction by generating speaker models (98) based on one or more speaker's speech; and by searching for speaker models (110) associated with one or more target speaker speech files.
The speaker repeats items (102).
Speaks English Native Native speaker · French Native Native speaker
A speaker independent (SI) Hidden Markov Model (HMM) engine, a speaker independent Dynamic Time Warping (DTW-SI) engine and a speaker dependent Dynamic Time Warping (DTW-SD) engine are combined.
The weighted sections of the utterances are used to convert a speaker independent model to a speaker dependent model.
A speaker independent mode provides flexibility to select desired commands from a predetermined list of speaker independent vocabulary.
Speaker registration section performs speaker registration based on compensated value from compensator.
The speech-recognition processor (12) can recognize the keywords independent of the speaker or may be trained for speaker-dependent recognition.
The speaker pronounces at least one code word which is compared to at least one pattern.
The template database includes one set of speaker independent templates and two sets of speaker dependent templates.
The invention relates to a method for verifying a speaker with a computer.
Moreover, by representing a speaker-dependent expression by speaker-independent training data, an environmental adaptation is inherently provided.
Everyone knows the “close talker” except the close talker himself.
In this manner the processor synthesizes an audio-visual representation of the speaker's face that is properly synchronized with the speaker's speech.
In certain embodiments of the invention, the invention is an integrated speaker training and speaker verification system that performs both training and speaker verification.
The speaker dependent model is represented by a speaker dependent Gaussian mixture model which is constructed using the linear transform matrices associated with the corresponding mixtures in the speaker independent model.
Requêtes fréquentes français :1-200, -1k, -2k, -3k, -4k, -5k, -7k, -10k, -20k, -40k, -100k, -200k, -500k, -1000k,
Requêtes fréquentes anglais :1-200, -1k, -2k, -3k, -4k, -5k, -7k, -10k, -20k, -40k, -100k, -200k, -500k, -1000k,
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