Phonetic Classification and Recognition Using the Multi-Layer Perceptron
Abstract
In this paper, we will describe several extensions to our earlier work, utiliz(cid:173) ing a segment-based approach. We will formulate our segmental framework and report our study on the use of multi-layer perceptrons for detection and classification of phonemes. We will also examine the outputs of the network, and compare the network performance with other classifiers. Our investigation is performed within a set of experiments that attempts to recognize 38 vowels and consonants in American English independent of speaker. When evaluated on the TIMIT database, our system achieves an accuracy of 56%.
Cite
Text
Leung et al. "Phonetic Classification and Recognition Using the Multi-Layer Perceptron." Neural Information Processing Systems, 1990.Markdown
[Leung et al. "Phonetic Classification and Recognition Using the Multi-Layer Perceptron." Neural Information Processing Systems, 1990.](https://mlanthology.org/neurips/1990/leung1990neurips-phonetic/)BibTeX
@inproceedings{leung1990neurips-phonetic,
title = {{Phonetic Classification and Recognition Using the Multi-Layer Perceptron}},
author = {Leung, Hong C. and Glass, James R. and Phillips, Michael S. and Zue, Victor W.},
booktitle = {Neural Information Processing Systems},
year = {1990},
pages = {248-254},
url = {https://mlanthology.org/neurips/1990/leung1990neurips-phonetic/}
}