SPEAKER RECOGNITION VIA VOICE SAMPLE BASED ON MULTIPLE NEAREST NEIGHBOR CLASSIFIERS

摘要

A speaker recognition system generates a codebook store with codebooks representing voice samples of speaker, referred to as trainers. The speaker recognition system may use multiple classifiers and generate a codebook store for each classifier. Each classifier uses a different set of features of a voice sample as its features. A classifier inputs a voice sample of an person and tries to authenticate or identify the person. A classifier generates a sequence of feature vectors for the input voice sample and then a code vector for that sequence. The classifier uses its codebook store to recognize the person. The speaker recognition system then combines the scores of the classifiers to generate an overall score. If the score satisfies a recognition criterion, then the speaker recognition system indicates that the voice sample is from that speaker.