Независимая система распознавания речи с использованием нейронных сетей

Н. У. Махешвари, А. П. Кабилан, Р. Венкатеш

 

 

Speaker Independent Speech Recognition System Using Neural Networks

 

N.Uma Maheswari¹, A.P.Kabilan² , R.Venkatesh³  

 

¹Senior Lecturer, Dept. of CSE, P.S.N.A College of Engg& Technology, Dindigul-624622,India

²Principal, Chettinad college of Engg& Technology, Karur-639114,India

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.

 

Keywords: speaker independent speech recognition, Neural Network, Hidden Markov Model, phonemes.