Noise spectrum estimation in adverse environments: improved minima controlled recursive averaging
Top Cited Papers
- 26 August 2003
- journal article
- Published by Institute of Electrical and Electronics Engineers (IEEE) in IEEE Transactions on Speech and Audio Processing
- Vol. 11 (5), 466-475
- https://doi.org/10.1109/tsa.2003.811544
Abstract
Noise spectrum estimation is a fundamental component of speech enhancement and speech recognition systems. We present an improved minima controlled recursive averaging (IMCRA) approach, for noise estimation in adverse environments involving nonstationary noise, weak speech components, and low input signal-to-noise ratio (SNR). The noise estimate is obtained by averaging past spectral power values, using a time-varying frequency-dependent smoothing parameter that is adjusted by the signal presence probability. The speech presence probability is controlled by the minima values of a smoothed periodogram. The proposed procedure comprises two iterations of smoothing and minimum tracking. The first iteration provides a rough voice activity detection in each frequency band. Then, smoothing in the second iteration excludes relatively strong speech components, which makes the minimum tracking during speech activity robust. We show that in nonstationary noise environments and under low SNR conditions, the IMCRA approach is very effective. In particular, compared to a competitive method, it obtains a lower estimation error, and when integrated into a speech enhancement system achieves improved speech quality and lower residual noise.Keywords
This publication has 15 references indexed in Scilit:
- Model based speech pause detectionPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2002
- Quantile based noise estimation for spectral subtraction and Wiener filteringPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2002
- Speech enhancement for non-stationary noise environmentsSignal Processing, 2001
- Assessing local noise level estimation methods: Application to noise robust ASRSpeech Communication, 2001
- Noise estimation techniques for robust speech recognitionPublished by Institute of Electrical and Electronics Engineers (IEEE) ,1995
- Elimination of the musical noise phenomenon with the Ephraim and Malah noise suppressorIEEE Transactions on Speech and Audio Processing, 1994
- Assessment for automatic speech recognition: II. NOISEX-92: A database and an experiment to study the effect of additive noise on speech recognition systemsSpeech Communication, 1993
- Speech enhancement using a minimum mean-square error log-spectral amplitude estimatorIEEE Transactions on Acoustics, Speech, and Signal Processing, 1985
- Speech enhancement using a minimum-mean square error short-time spectral amplitude estimatorIEEE Transactions on Acoustics, Speech, and Signal Processing, 1984
- Speech enhancement using a soft-decision noise suppression filterIEEE Transactions on Acoustics, Speech, and Signal Processing, 1980