Matches in ScholarlyData for { <https://w3id.org/scholarlydata/inproceedings/lrec2008/papers/174> ?p ?o. }
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- 174 creator guillaume-gravier.
- 174 creator pascale-sebillot.
- 174 creator stephane-huet.
- 174 type InProceedings.
- 174 label "Morphosyntactic Resources for Automatic Speech Recognition".
- 174 sameAs 174.
- 174 abstract "Texts generated by automatic speech recognition (ASR) systems have some specificities, related to the idiosyncrasies of oral productions or the principles of ASR systems, that make them more difficult to exploit than more conventional natural language written texts. This paper aims at studying the interest of morphosyntactic information as a useful resource for ASR. We show the ability of automatic methods to tag outputs of ASR systems, by obtaining a tag accuracy similar for automatic transcriptions to the 95-98 % usually reported for written texts, such as newspapers. We also demonstrate experimentally that tagging is useful to improve the quality of transcriptions by using morphosyntactic information in a post-processing stage of speech decoding. Indeed, we obtain a significant decrease of the word error rate with experiments done on French broadcast news from the ESTER corpus; we also notice an improvement of the sentence error rate and observe that a significant number of agreement errors are corrected.".
- 174 hasAuthorList authorList.
- 174 hasTopic Linguistics.
- 174 isPartOf proceedings.
- 174 keyword "Language modelling".
- 174 keyword "Speech recognition and understanding".
- 174 keyword "Tagging".
- 174 title "Morphosyntactic Resources for Automatic Speech Recognition".