Title :
Speaker recognition with a MLP classifier and LPCC codebook
Author :
Rodriguez-Porcheron, Daniel ; Faundez-Zanuy, Marcos
Author_Institution :
Univ. Politecnica de Catalunya, Barcelona, Spain
Abstract :
This paper improves the speaker recognition rates of a MLP classifier and LPCC codebook alone, using a linear combination between both methods. In simulations we have obtained an improvement of 4.7% over a LPCC codebook of 32 vectors and 1.5% for a codebook of 128 vectors (error rate drops from 3.68% to 2.1%). Also we propose an efficient algorithm that reduces the computational complexity of the LPCC-VQ system by a factor of 4
Keywords :
computational complexity; linear predictive coding; multilayer perceptrons; signal classification; speaker recognition; speech coding; LPCC codebook; LPCC-VQ system; MLP classifier; computational complexity reduction; efficient algorithm; error rate; linear combination; multilayer preceptron; simulations; speaker recognition; vectors; Cepstral analysis; Classification tree analysis; Databases; Electronic mail; Hidden Markov models; Neural networks; Neurons; Speaker recognition; Vector quantization; World Wide Web;
Conference_Titel :
Acoustics, Speech, and Signal Processing, 1999. Proceedings., 1999 IEEE International Conference on
Conference_Location :
Phoenix, AZ
Print_ISBN :
0-7803-5041-3
DOI :
10.1109/ICASSP.1999.759872
