A real time speaker-independent continuous speech recognition system

Reports on the speaker-independent continuous speech recognition system with speaker adaptation. This system is based on continuous HMM with mixture Gaussian distribution, and several fast algorithms are applied for real time calculation. To reduce HMM states, the system uses the mono-state context dependent model, called acoustic phonetic segment. The calculation of mixture Gaussian distributions is reduced, by varying the number of mixtures dynamically. The fast Viterbi calculation algorithm with duration control is used. The system has been successfully implemented as a man-machine interface of the plant control expert system, achieving sentence accuracy of 98.7%