Phonetic Classification and Recognition Using the Multi-Layer Perceptron

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%.

Authors

• Hong Leung
• James Glass
• Michael Phillips
• Victor Zue

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