Combination of Multiple Speech Transcription Methods for Vocabulary Independent Search

Today, most systems use large vocabulary continuous speech recognition tools to produce word transcripts which have indexed transcripts and query terms retrieved from the index. However, query terms that are not part of the recognizer’s vocabulary cannot be retrieved, thereby affecting the recall of the search. Such terms can be retrieved using phonetic search methods. Phonetic transcripts can be generated by expanding the word transcripts into phones using the baseforms in the dictionary. In addition, advanced systems can provide phonetic transcripts using sub-word based language models. However, these phonetic transcripts suffer from inaccuracy and do not provide a good alternative to word transcripts. We demonstrate how to retrieve information from speech data by presenting a novel approach for vocabulary independent retrieval combining search on transcripts that are produced according to different word and sub-word decoding methods. We present two different algorithms: the first is based on the Threshold Algorithm (TA); the second uses a Boolean retrieval model on inverted indices. The value of this combination is demonstrated on data from NIST 2006 Spoken Term Detection evaluation.