Self-organized language modeling for speech recognition
Readings in speech recognition
Effects of out of vocabulary words in spoken document retrieval (poster session)
SIGIR '00 Proceedings of the 23rd annual international ACM SIGIR conference on Research and development in information retrieval
Indexing and retrieval of broadcast news
Speech Communication - Special issue on accessing information in spoken audio
The Cambridge University spoken document retrieval system
ICASSP '99 Proceedings of the Acoustics, Speech, and Signal Processing, 1999. on 1999 IEEE International Conference - Volume 01
Spoken term detection using fast phonetic decoding
ICASSP '09 Proceedings of the 2009 IEEE International Conference on Acoustics, Speech and Signal Processing
Rapid Yet Accurate Speech Indexing Using Dynamic Match Lattice Spotting
IEEE Transactions on Audio, Speech, and Language Processing
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Spoken term detection (STD) popularly involves performing word or sub-word level speech recognition and indexing the result. This work challenges the assumption that improved speech recognition accuracy implies better indexing for STD. Using an index derived from phone lattices, this paper examines the effect of language model selection on the relationship between phone recognition accuracy and STD accuracy. Results suggest that language models usually improve phone recognition accuracy but their inclusion does not always translate to improved STD accuracy. The findings suggest that using phone recognition accuracy to measure the quality of an STD index can be problematic, and highlight the need for an alternative that is more closely aligned with the goals of the specific detection task.