Abstract
This paper summarizes our acoustic modeling efforts in the Johns Hopkins University speech recognition system for the CHiME-5 challenge to recognize highly-overlapped dinner party speech recorded by multiple microphone arrays. We explore data augmentation approaches, neural network architectures, front-end speech dereverberation, beamforming and robust i-vector extraction with comparisons of our in-house implementations and publicly available tools. We finally achieved a word error rate of 69.4% on the development set, which is a 11.7% absolute improvement over the previous baseline of 81.1%, and release this improved baseline with refined techniques/tools as an advanced CHiME-5 recipe.
| Original language | English |
|---|---|
| Title of host publication | 2019 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2019 - Proceedings |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| Pages | 6665-6669 |
| Number of pages | 5 |
| ISBN (Electronic) | 9781479981311 |
| DOIs | |
| Publication status | Published - 2019 May 1 |
| Event | 44th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2019 - Brighton, United Kingdom Duration: 2019 May 12 → 2019 May 17 |
Publication series
| Name | ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings |
|---|---|
| Volume | 2019-May |
| ISSN (Print) | 1520-6149 |
Conference
| Conference | 44th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2019 |
|---|---|
| Country | United Kingdom |
| City | Brighton |
| Period | 19/5/12 → 19/5/17 |
Fingerprint
Keywords
- acoustic modeling
- CHiME-5 challenge
- Kaldi
- Robust speech recognition
ASJC Scopus subject areas
- Software
- Signal Processing
- Electrical and Electronic Engineering
Cite this
Acoustic Modeling for Overlapping Speech Recognition : Jhu Chime-5 Challenge System. / Manohar, Vimal; Chen, Szu Jui; Wang, Zhiqi; Fujita, Y.; Watanabe, Shinji; Khudanpur, Sanjeev.
2019 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2019 - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2019. p. 6665-6669 8682556 (ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings; Vol. 2019-May).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - Acoustic Modeling for Overlapping Speech Recognition
T2 - Jhu Chime-5 Challenge System
AU - Manohar, Vimal
AU - Chen, Szu Jui
AU - Wang, Zhiqi
AU - Fujita, Y.
AU - Watanabe, Shinji
AU - Khudanpur, Sanjeev
PY - 2019/5/1
Y1 - 2019/5/1
N2 - This paper summarizes our acoustic modeling efforts in the Johns Hopkins University speech recognition system for the CHiME-5 challenge to recognize highly-overlapped dinner party speech recorded by multiple microphone arrays. We explore data augmentation approaches, neural network architectures, front-end speech dereverberation, beamforming and robust i-vector extraction with comparisons of our in-house implementations and publicly available tools. We finally achieved a word error rate of 69.4% on the development set, which is a 11.7% absolute improvement over the previous baseline of 81.1%, and release this improved baseline with refined techniques/tools as an advanced CHiME-5 recipe.
AB - This paper summarizes our acoustic modeling efforts in the Johns Hopkins University speech recognition system for the CHiME-5 challenge to recognize highly-overlapped dinner party speech recorded by multiple microphone arrays. We explore data augmentation approaches, neural network architectures, front-end speech dereverberation, beamforming and robust i-vector extraction with comparisons of our in-house implementations and publicly available tools. We finally achieved a word error rate of 69.4% on the development set, which is a 11.7% absolute improvement over the previous baseline of 81.1%, and release this improved baseline with refined techniques/tools as an advanced CHiME-5 recipe.
KW - acoustic modeling
KW - CHiME-5 challenge
KW - Kaldi
KW - Robust speech recognition
UR - http://www.scopus.com/inward/record.url?scp=85068973715&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85068973715&partnerID=8YFLogxK
U2 - 10.1109/ICASSP.2019.8682556
DO - 10.1109/ICASSP.2019.8682556
M3 - Conference contribution
AN - SCOPUS:85068973715
T3 - ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
SP - 6665
EP - 6669
BT - 2019 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2019 - Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
ER -