Search algorithm that merges candidates in meaning level for very large vocabulary spontaneous speech recognition

The paper describes an efficient search algorithm for spontaneous speech recognition. This algorithm merges candidates that have the same meaning in beam search. To do this effectively, the authors change their phoneme-synchronous search algorithm into a quasi-frame-synchronous one. The algorithm is evaluated using a telephone directory assistance task containing more than 70000 subscriber names. The average sentence understanding rate for eight speakers is improved from 58% to 65% by merging candidates at the meaning level