Discriminative named entity recognition of speech data using speech recognition confidence
نویسندگان
چکیده
This paper presents a method for the named entity recognition (NER) of speech data that uses automatic speech recognition (ASR) confidence as a feature that indicates whether each word is correctly recognized. An NER model is trained using ASR results with named entity (NE) labels to include an ASR confidence feature as well as corresponding transcriptions with NE labels. Experiments using support vector machines (SVMs) and speech data from Japanese newspaper articles show that the proposed method achieves higher F-measure in NER than a simple application of text-based NER to ASR results.
منابع مشابه
Incorporating Speech Recognition Confidence into Discriminative Named Entity Recognition of Speech Data
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...
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