DocumentCode :
3141672
Title :
ASR post-processing correction based on NER and pronunciation primitive
Author :
Jun, Jiang ; Lei, Li
Author_Institution :
Intell. Technol. Res. Center, Beijing Univ. of Posts & Telecommun., Beijing, China
fYear :
2011
fDate :
27-29 Nov. 2011
Firstpage :
126
Lastpage :
131
Abstract :
In dealing with robustness of specific areas,such as automatic speech recognition (ASR).this paper proposes some new ideas. The idea of using named entity recognition(NER), which is domain-specific is based on the conditional random field(CRF).NE are used to establish the context, leading the speech recognition process´ pronunciation element into the post-treatment of speech recognition, Speech recognition results are represented with pronunciation primitive characters. And based on the improved dynamic edit distance we find the appropriate entity context, and then according to the context of the entity we try to optimize the recognition results.
Keywords :
speech recognition; ASR post-processing correction; automatic speech recognition; conditional random field; dynamic edit distance; entity context; named entity recognition; pronunciation primitive; Accuracy; Biological system modeling; Bismuth; Manuals; Robustness; Speech recognition; conditional random field; entity context; improved dynamic edit distance; named entity recognition; pronunciation primitive;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Natural Language Processing andKnowledge Engineering (NLP-KE), 2011 7th International Conference on
Conference_Location :
Tokushima
Print_ISBN :
978-1-61284-729-0
Type :
conf
DOI :
10.1109/NLPKE.2011.6138180
Filename :
6138180
Link To Document :
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