Method of denoising an audio signal

• US 20070276660A1
• Filed: 02/26/2007
• Published: 11/29/2007
• Est. Priority Date: 03/01/2006
• Status: Active Grant

• Current Assignee: Parrot Automotive
• Original Assignee: Parrot Societe Anonyme
• Inventors: Pinto, Guillaume
• Granted Patent: US 7,953,596 B2
• Time in Patent Office: Days
• US Class Current: 704/219
• CPC Class Codes: G10L 21/0208 Noise filtering

Abstract

This method is a method of analyzing time coherence in the noisy signal and comprises the steps consisting in: a) determining a reference signal from the noisy signal by applying treatment (10, 18) to the noisy signal that is suitable for attenuating speech components more strongly than the noise component, in particular by means of an adaptive recursive predictive algorithm of the LMS type; b) determining (24) a probability of speech being present/absent on the basis of the respective energy levels in the spectral domain of the noisy signal and of the reference signal; and c) deriving (26) a denoised estimate of the speech signal from the noise signal as a function of the probability of the speech being present/absent as determined in this way.

Claims

1. A method of processing an audio signal for denoising a noisy signal that comprises a speech component in combination with a noise component, the noise component itself comprising a transient noise component and a pseudo-steady noise component,

the method being characterized in that it is a method of analyzing time coherence of the sampled noisy signal comprising the steps of:

a) determining a reference signal by applying processing (10, 18) to the noisy signal suitable for attenuating the speech components more strongly than the noise components in said noisy signal, said processing comprising;

a1) applying an adaptive linear prediction algorithm operating on a linear combination of earlier samples of the noisy signal; and

a2) determining said reference signal by taking the difference, with compensation for phase offset, between the noisy signal and the signal delivered by the linear prediction algorithm;

b) determining (24) an a priori probability of speech being present/absent on the basis of the respective energy levels in the spectral domain of the noisy signal and of the reference signal; and

c) using said a priori probability of the absence of speech to estimate a noise spectrum and deriving (26) from the noisy signal a denoised estimate of the speech signal.

2. The method of claim 1, in which said reference signal is determined by applying in step a2) a relationship of the type:

3. The method of claim 1, in which the linear prediction algorithm (10) is an algorithm of the least mean square (LMS) type.

4. The method of claim 1, in which the linear prediction algorithm (10) is a recursive adaptive algorithm.

5. The method of claim 1, in which step b) comprises an algorithm for estimating the energy of the pseudo-steady noise component in the reference signal and in the noisy signal.

6. The method of claim 5, in which the algorithm for estimating the energy of the pseudo-steady noise component is an algorithm of the minima controlled recursive averaging (MRCA) type.

7. The method of claim 1, in which step c) comprises applying a variable gain algorithm that is a function of the probability of speech being present/absent.

8. The method of claim 7, in which the variable gain algorithm is an algorithm of the optimally-modified log-spectral amplitude (OM-LSA) gain type.