14th International Congress of Phonetic Sciences (ICPhS-14)
San Francisco, CA, USA
An automatic system, Rasta-PLP and Recurrent Neural Network based, for classifying vowels, fricatives and nasals from TIMIT has been built up. A new philosophy based on the idea to use a short piece of the available signal was implemented in the preprocessing phase. This allowed to save memory space and computational time. On the testing data, the results gave the 98.5% of correct classification for vowels and fricatives, and the 97% of correct classification for nasals. These results are significant considering that they have been obtained using only 30 msec of the signal available.
Bibliographic reference. Esposito, Anna / Ceglia, R. (1999): "Phonemes classification with recurrent neural networks", In ICPhS-14, 707-710.