Unsupervised speaker classification using self-organizing maps (SOM)

An algorithm for unsupervised speaker classification using Kohonen SOM is presented. The system employs 6/spl times/10 SOM networks for each speaker and for non-speech segments. The algorithm was evaluated using high quality as well as telephone quality conversations between two speakers. Correct classification of more than 90% was demonstrated. High quality conversation between three speakers yielded 80% correct classification. The high quality speech required the use of 12/sup th/ order cepstral coefficients vector. In telephone quality speech, an additional 12 features of the difference of the cepstrum were required.