A neural speaker model for speaker clustering
Satoshi Nakamura, Toshio Akabane · 1991
A speaker model using a neural network is proposed for reference speaker clustering on speaker independent speech recognition. Speaker individuality is embedded in not only a static short time spectrum and a pitch frequency, but also a dynamic spectral pattern and pitch pattern. In conventional modeling, speaker individuality is based on the former static features. The authors try to capture the latter dynamic features, of speaker by a neural speaker model. Two methods, neural prediction modeling by multilayer perceptron and learning matrix vector-quantization, are considered for the speaker modeling. Using the measures of speaker modeling, speaker clustering of the reference patterns based on mutual information is carried out for speaker independent speech recognition.>