8th Annual Conference of the International Speech Communication Association

Antwerp, Belgium
August 27-31, 2007

Morphosyntactic Processing of N-Best Lists for Improved Recognition and Confidence Measure Computation

Stéphane Huet, Guillaume Gravier, Pascale Sébillot

IRISA, France

We study the use of morphosyntactic knowledge to process N-best lists. We propose a new score function that combines the parts of speech (POS), language model, and acoustic scores at the sentence level. Experimental results, obtained for French broadcast news transcription, show a significant improvement of the word error rate with various decoding criteria commonly used in speech recognition. Interestingly, we observed more grammatical transcriptions, which translates into a better sentence error rate. Finally, we show that POS knowledge also improves posterior based confidence measures.

Full Paper

Bibliographic reference.  Huet, Stéphane / Gravier, Guillaume / Sébillot, Pascale (2007): "Morphosyntactic processing of n-best lists for improved recognition and confidence measure computation", In INTERSPEECH-2007, 1741-1744.