система распознавания речи с использованием нейронных сетей
У. Махешвари, А. П. Кабилан, Р. Венкатеш
Speaker Independent Speech Recognition System Using
N.Uma Maheswari1, A.P.Kabilan2
1Senior Lecturer, Dept. of CSE, P.S.N.A College of Engg& Technology, Dindigul-624622,India
2Principal, Chettinad college of Engg&
3Senior Lecturer, Dept. of CSE, R.V.S College of Engg& Technology, Dindigul-624005,India
Received July 4, 2009
Speaker independent 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 2000 words uttered by 100 speakers. The test samples comprised 1000
words spoken by a different set of 50 speakers. The recognition accuracy is
found to be 92% which is well above the previous results.
speaker independent speech
recognition, Neural Network, Hidden Markov Model, phonemes.