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Dependency of recognition rate on number of words for text‐independent speaker recognition using vector quantization
2008
Journal of the Acoustical Society of America
Acoustics 08 Paris speaker consists of a feature map. Two kinds of feature vector MFCC and FTTSS of each speaker are used for training the map, and they are quantized into a specific vector on the feature map. The feature FTTSS is used to develop a robust speaker recognition system under noisy condition. Using the map, we conduct speaker recognition(identification and verification) based on vector quantization (VQ) distortion. In particular we examine dependency of recognition rates on number
doi:10.1121/1.2935784
fatcat:g6sjywcah5dtdift3hvdtujhf4