A multi-lingual speech recognition system using a neural network approach
O.T.-C. Chen, Chih-Yung Chen, Hwai-Tsu Chan, Fang-Ru Hsu, Huang-Lin Yang, Youn-Gwo Lee · 2002
A learning vector quantization method based on the dynamic time warping scheme is proposed for the speech recognition. The optimized speech database and adequate time-alignment vector matching can be achieved. The recognition accuracy for different users is improved by adapting the speech database using the learning vector quantization method. An user-friendly software system of the proposed method is implemented to demonstrate the recognition of 200 voice commands. Various languages and dialects can be realized in our system with a high recognition accuracy. The evaluation board of speech recognition using an 8051 microprocessor has been designed for the industrial applications. A pipelined programmable micro-architecture of the speech recognition processor is developed for the high-performance and high-speed recognition system.