Fundamentals of speech recognition
Fundamentals of speech recognition
Pattern Recognition with Fuzzy Objective Function Algorithms
Pattern Recognition with Fuzzy Objective Function Algorithms
Advances in Speech Signal Processing
Advances in Speech Signal Processing
High-accuracy connected digit recognition for mobile applications
ICASSP '96 Proceedings of the Acoustics, Speech, and Signal Processing, 1996. on Conference Proceedings., 1996 IEEE International Conference - Volume 01
| Hi-index | 0.00 |
This paper proposes a robust, speaker-independent isolated word speech recognition (IWSR) system (SMQ/HMM_SVQ/HMM)/MLP which combines Dual Split Matrix Quantization (SMQ) and Split Vector Quantization (SVQ) pair combined with both the strength of HMM in modeling stochastic sequences and the non-linear classification capability of MLP neural networks (NN). The system efficiently utilizes processing resources and improves speech recognition performance by using neural networks as the classifier of the system. Computer simulation clearly indicates superiority over conventional VQ/HMM and MQ/HMM systems with 98% and 95.8% recognition accuracy at 20 dB and 5 dB SNR levels, respectively in a car noise environment, based on the database TIDIGIT.