Speech Recognition System Based On Phonemes Using Neural Networks

Speech recognition is important for successful development of speech recognizers in most real world applications. While speaker dependent speech recognizers have achieved close to 100% accuracy, the speaker independent speech recognition systems have poor accuracy not exceeding 75%.In this paper we describe a two-module speaker independent speech recognition system for all-British English speech. The first module performs phoneme recognition using two-level neural networks. The second module executes word recognition from the string of phonemes employing Hidden Markov Model. The system was trained by British English speech consisting of 5000 words uttered by 100 speakers. The test samples comprised 2000 words spoken by a different set of 50 speakers. The recognition accuracy is found to be 98% which is well above the previous results.

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