September 22-25, 1997
For many years, the K-Nearest Neighbours method (K-NN) is known as one of the best probability density function (pdf) estimator. A fast K-NN algorithm has been developed and tested on the TIMIT database with a gain in computational time of 99;8%. The K-NN decision principle has been assessed on a frame by frame phonetic identification. A method to integrate K-NN estimator pdf in a HMM-based system is proposed and tested on an acoustic-phonetic decoding task. Finally, preliminary experiments are performed on the HMM topology inference.
Bibliographic reference. Montacié, Claude / Caraty, Marie-José / Lefèvre, Fabrice (1997): "K-NN versus Gaussian in HMM-based recognition system", In EUROSPEECH-1997, 529-532.