Abstract
An accurate estimation of the broadband input signal-to-noise ratio (SNR) is a prerequisite for many hearing-aid algorithms. An extensive comparison of three SNR estimation algorithms was performed. Moreover, the influence of the duration of the analysis window on the SNR estimation performance was systematically investigated.
The most accurate approach utilized an estimation of the clean speech power spectral density (PSD) and the noisy speech power across a sliding window of 1280 ms and achieved an total SNR estimation error below 3 dB across a wide variety of background noises and input SNRs
The most accurate approach utilized an estimation of the clean speech power spectral density (PSD) and the noisy speech power across a sliding window of 1280 ms and achieved an total SNR estimation error below 3 dB across a wide variety of background noises and input SNRs
Original language | English |
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Title of host publication | Proceedings of ICASSP 2017 |
Publisher | IEEE |
Publication date | 2017 |
Pages | 231-235 |
ISBN (Print) | 978-1-5090-4117-6 |
DOIs | |
Publication status | Published - 2017 |
Event | 2017 IEEE International Conference on Acoustics, Speech and Signal Processing - Hilton New Orleans Riverside, New Orleans, United States Duration: 5 Mar 2017 → 9 Mar 2017 Conference number: 42 http://www.ieee-icassp2017.org/ |
Conference
Conference | 2017 IEEE International Conference on Acoustics, Speech and Signal Processing |
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Number | 42 |
Location | Hilton New Orleans Riverside |
Country/Territory | United States |
City | New Orleans |
Period | 05/03/2017 → 09/03/2017 |
Internet address |
Keywords
- Signal-to-noise ratio estimation
- Noise power estimation
- Hearing-aid algorithms