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Abstract
In this paper we present an extension of our previously described neural machine translation based system for punctuated transcription. This extension allows the system to map from per frame acoustic features to word level representations by replacing the traditional encoder in the encoder-decoder architecture with a hierarchical encoder. Furthermore, we show that a system combining lexical and acoustic features significantly outperforms systems using only a single source
of features on all measured punctuation marks. The combination of lexical and acoustic features achieves a significant improvement in F-Measure of 1.5 absolute over the purely lexical neural machine translation based system.
of features on all measured punctuation marks. The combination of lexical and acoustic features achieves a significant improvement in F-Measure of 1.5 absolute over the purely lexical neural machine translation based system.
Original language | English |
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Title of host publication | The 42nd IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2017) |
Publisher | Institute of Electrical and Electronics Engineers (IEEE) |
Pages | 5700-5704 |
Number of pages | 5 |
ISBN (Print) | 978-1-5090-4117-6 |
DOIs | |
Publication status | Published - 19 Jun 2017 |
Event | 42nd IEEE International Conference on Acoustics, Speech and Signal Processing - New Orleans, United States Duration: 5 Mar 2017 → 9 Mar 2017 http://www.ieee-icassp2017.org/ |
Publication series
Name | |
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Publisher | IEEE |
ISSN (Electronic) | 2379-190X |
Conference
Conference | 42nd IEEE International Conference on Acoustics, Speech and Signal Processing |
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Abbreviated title | ICASSP 2017 |
Country/Territory | United States |
City | New Orleans |
Period | 5/03/17 → 9/03/17 |
Internet address |
Fingerprint
Dive into the research topics of 'Sequence-to-Sequence Models for Punctuated Transcription Combing Lexical and Acoustic Features'. Together they form a unique fingerprint.Projects
- 1 Finished
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SUMMA - Scalable Understanding of Mulitingual Media
Renals, S., Birch-Mayne, A. & Cohen, S.
1/02/16 → 31/01/19
Project: Research