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Proper Name Retrieval from Diachronic Documents for Automatic Speech Transcription using Lexical and Temporal Context
Abstract : Proper names are usually key to understanding the information contained in a document. Our work focuses on increasing the vocabulary coverage of a speech transcription system by automatically retrieving new proper names from contemporary diachronic text documents. The idea is to use in-vocabulary proper names as an anchor to collect new linked proper names from the diachronic corpus. Our assumption is that time is an important feature for capturing name-to-context dependencies, that was confirmed by temporal mismatch experiments. We studied a method based on Mutual Information and proposed a new method based on cosine-similarity measure that dynamically augment the automatic speech recognition system vocabulary. Recognition results show a significant reduction of the word error rate using augmented vocabulary for broadcast news transcription.
Cited literature [16 references]
https://hal.inria.fr/hal-01092224
Contributor : Dominique Fohr Connect in order to contact the contributor
Submitted on : Monday, December 8, 2014 - 2:25:09 PM
Last modification on : Friday, February 26, 2021 - 3:28:06 PM
Long-term archiving on: : Monday, March 9, 2015 - 11:45:51 AM
Contributor : Dominique Fohr Connect in order to contact the contributor
Submitted on : Monday, December 8, 2014 - 2:25:09 PM
Last modification on : Friday, February 26, 2021 - 3:28:06 PM
Long-term archiving on: : Monday, March 9, 2015 - 11:45:51 AM
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slam2014_final.pdf
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