Title
Incorporating speech recognition confidence into discriminative named entity recognition of speech data
Abstract
This paper proposes a named entity recognition (NER) method for speech recognition results that uses confidence on automatic speech recognition (ASR) as a feature. The ASR confidence feature indicates whether each word has been correctly recognized. The NER model is trained using ASR results with named entity (NE) labels as well as the corresponding transcriptions with NE labels. In experiments using support vector machines (SVMs) and speech data from Japanese newspaper articles, the proposed method outperformed a simple application of text-based NER to ASR results in NER F-measure by improving precision. These results show that the proposed method is effective in NER for noisy inputs.
Year
DOI
Venue
2006
10.3115/1220175.1220253
ACL
Keywords
Field
DocType
automatic speech recognition,incorporating speech recognition confidence,asr confidence feature,text-based ner,speech recognition result,speech data,entity recognition,ner f-measure,asr result,ner model,speech recognition,support vector machine
Transcription (linguistics),Computer science,Support vector machine,Named entity,Speech recognition,Artificial intelligence,Natural language processing,Discriminative model,Named-entity recognition
Conference
Volume
Citations 
PageRank 
P06-1
12
0.77
References 
Authors
16
3
Name
Order
Citations
PageRank
Katsuhito Sudoh132634.44
Hajime Tsukada244929.46
Hideki Isozaki393464.50