Experiments on mixture-density phoneme-modelling for the speaker-independent 1000-word speech recognition DARPA task

The modifications and improvements of the acoustic recognition component of the SPICOS system for the DARPA naval resource management task are described. These modifications and improvements include: the modeling of the continuous mixture densities of the acoustic vectors, the choice of suitable context-dependent phoneme units and the construction of generalized context phoneme units, and the modeling of transitional information in the acoustic vector. The experimental results show that critical factors are the acoustic resolution of the probability distributions and the context information captured in the acoustic vectors. By these enhancements, the system was able to attain a word error rate of 23.6% and 26.5% on two test sets in speaker-independent recognition mode, when trained on 80 speakers. The word pair grammar reduced the word error rate to 7.1% and 9.3% respectively