Details
| Original language | English |
|---|---|
| Title of host publication | 2019 IEEE International Conference on Acoustics, Speech, and Signal Processing |
| Subtitle of host publication | Proceedings |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| Pages | 211-215 |
| Number of pages | 5 |
| ISBN (electronic) | 9781479981311 |
| ISBN (print) | 9781479981328 |
| Publication status | Published - 17 Apr 2019 |
| Event | 44th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2019 - Brighton, United Kingdom (UK) Duration: 12 May 2019 → 17 May 2019 |
Publication series
| Name | International Conference on Acoustics, Speech, and Signal Processing (ICASSP) |
|---|---|
| ISSN (Print) | 1520-6149 |
| ISSN (electronic) | 2379-190X |
Abstract
Reverberation time is an important room acoustical parameter that can be used to identify the acoustic environment, predict speech intelligibility and model the late reverberation for binaural rendering, etc. Several blind estimation algorithms of reverberation time have been proposed by analyzing recorded speech signals. Unfortunately, the estimation accuracy for the frequency dependent reverberation time is lower than for the full-band reverberation time due to the lower signal energy in sub-band filters. This study presents a novel approach for the blind estimation of reverberation time in the full frequency range. The maximum likelihood method is applied for the estimation of the reverberation time from low- to mid-frequencies, and the reverberation time from mid- to high-frequencies is predicted by our proposed model based on the analysis of the reverberation time calculated from room impulse responses in different rooms. The proposed method is validated by two experiments and shows a good performance.
Keywords
- blind estimation, full frequency range, reverberation time, room acoustics, speech signals
ASJC Scopus subject areas
- Computer Science(all)
- Software
- Computer Science(all)
- Signal Processing
- Engineering(all)
- Electrical and Electronic Engineering
Cite this
- Standard
- Harvard
- Apa
- Vancouver
- BibTeX
- RIS
2019 IEEE International Conference on Acoustics, Speech, and Signal Processing: Proceedings. Institute of Electrical and Electronics Engineers Inc., 2019. p. 211-215 (International Conference on Acoustics, Speech, and Signal Processing (ICASSP)).
Research output: Chapter in book/report/conference proceeding › Conference contribution › Research › peer review
}
TY - GEN
T1 - A Hybrid Method for Blind Estimation of Frequency Dependent Reverberation Time Using Speech Signals
AU - Li, Song
AU - Schlieper, Roman
AU - Peissig, Jurgen
N1 - Funding information: This work is supported by Huawei Innovation Research Program FLAGSHIP (HIRP FLAGSHIP) project.
PY - 2019/4/17
Y1 - 2019/4/17
N2 - Reverberation time is an important room acoustical parameter that can be used to identify the acoustic environment, predict speech intelligibility and model the late reverberation for binaural rendering, etc. Several blind estimation algorithms of reverberation time have been proposed by analyzing recorded speech signals. Unfortunately, the estimation accuracy for the frequency dependent reverberation time is lower than for the full-band reverberation time due to the lower signal energy in sub-band filters. This study presents a novel approach for the blind estimation of reverberation time in the full frequency range. The maximum likelihood method is applied for the estimation of the reverberation time from low- to mid-frequencies, and the reverberation time from mid- to high-frequencies is predicted by our proposed model based on the analysis of the reverberation time calculated from room impulse responses in different rooms. The proposed method is validated by two experiments and shows a good performance.
AB - Reverberation time is an important room acoustical parameter that can be used to identify the acoustic environment, predict speech intelligibility and model the late reverberation for binaural rendering, etc. Several blind estimation algorithms of reverberation time have been proposed by analyzing recorded speech signals. Unfortunately, the estimation accuracy for the frequency dependent reverberation time is lower than for the full-band reverberation time due to the lower signal energy in sub-band filters. This study presents a novel approach for the blind estimation of reverberation time in the full frequency range. The maximum likelihood method is applied for the estimation of the reverberation time from low- to mid-frequencies, and the reverberation time from mid- to high-frequencies is predicted by our proposed model based on the analysis of the reverberation time calculated from room impulse responses in different rooms. The proposed method is validated by two experiments and shows a good performance.
KW - blind estimation
KW - full frequency range
KW - reverberation time
KW - room acoustics
KW - speech signals
UR - http://www.scopus.com/inward/record.url?scp=85068992204&partnerID=8YFLogxK
U2 - 10.1109/ICASSP.2019.8682661
DO - 10.1109/ICASSP.2019.8682661
M3 - Conference contribution
AN - SCOPUS:85068992204
SN - 9781479981328
T3 - International Conference on Acoustics, Speech, and Signal Processing (ICASSP)
SP - 211
EP - 215
BT - 2019 IEEE International Conference on Acoustics, Speech, and Signal Processing
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 44th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2019
Y2 - 12 May 2019 through 17 May 2019
ER -