论文信息 - AN EFFICIENT ONE-PASS DECODER FOR FINNISH LARGE VOCABULARY CONTINUOUS SPEECH RECOGNITION

AN EFFICIENT ONE-PASS DECODER FOR FINNISH LARGE VOCABULARY CONTINUOUS SPEECH RECOGNITION

This paper describes a design of a one-pass large vocabulary continuous speech recognition decoder aimed for Finnish. The decoder is based on the popular time-synchronous beam search approach, extended to handle some language dependent issues. For the construction of the static part of the search network a new algorithm is presented, which enables efficient use of shared state HMMs. The search network also includes statically expanded cross-word triphone contexts, which increase the memory requirements only modestly. The beam search is enhanced with a bigram language model look-ahead technique, implemented using simple table lookups and an efficient caching scheme. Compared to our previous decoder, the new design achieves 24% relative reduction to phoneme error rate, with a near real-time performance.

Janne Pylkkönen

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