Publication Details
Title: Estimation of Noise Spectrum and its Application to SNR-Estimation and Speech Enhancement
Author: H.-G. Hirsch
Bibliographic Information: ICSI Technical Report TR-93-012
Date: March 1993
Research Area: [Research Area not defined]
Type: Technical Reports
PDF: ftp://ftp.icsi.berkeley.edu/pub/techreports/1993/tr-93-012.pdf
Overview:
One possible solution to improve recognition of noisy speech is the application of noise reduction techniques. Spectral subtraction is one well known technique to reduce stationary background noise in case of recording with a single microphone. An estimation of the noise spectrum is necessary to apply this method. The determination of segments containing just noise is usually a difficult task. This report describes a method to estimate the noise spectrum without the need of distinguishing between segments of noisy speech and segments of pure noise. The estimation of noise power inside one subband is based on an analysis of the histogram of a certain number of past short-term energy values inside this subband. This technique for estimating the noise spectrum can be used to estimate the actual signal-to-noise ratio (SNR). Another application is the integration inside a spectral subtraction technique for speech enhancement.
Bibliographic Reference:
H.-G. Hirsch. Estimation of Noise Spectrum and its Application to SNR-Estimation and Speech Enhancement. ICSI Technical Report TR-93-012, March 1993
Author: H.-G. Hirsch
Bibliographic Information: ICSI Technical Report TR-93-012
Date: March 1993
Research Area: [Research Area not defined]
Type: Technical Reports
PDF: ftp://ftp.icsi.berkeley.edu/pub/techreports/1993/tr-93-012.pdf
Overview:
One possible solution to improve recognition of noisy speech is the application of noise reduction techniques. Spectral subtraction is one well known technique to reduce stationary background noise in case of recording with a single microphone. An estimation of the noise spectrum is necessary to apply this method. The determination of segments containing just noise is usually a difficult task. This report describes a method to estimate the noise spectrum without the need of distinguishing between segments of noisy speech and segments of pure noise. The estimation of noise power inside one subband is based on an analysis of the histogram of a certain number of past short-term energy values inside this subband. This technique for estimating the noise spectrum can be used to estimate the actual signal-to-noise ratio (SNR). Another application is the integration inside a spectral subtraction technique for speech enhancement.
Bibliographic Reference:
H.-G. Hirsch. Estimation of Noise Spectrum and its Application to SNR-Estimation and Speech Enhancement. ICSI Technical Report TR-93-012, March 1993