Method of denoising a noisy signal including speech and noise components

• US 7,953,596 B2
• Filed: 02/26/2007
• Issued: 05/31/2011
• Est. Priority Date: 03/01/2006
• Status: Active Grant

• Current Assignee: Parrot Automotive
• Original Assignee: Parrot Societe Anonyme
• Inventors: Pinto, Guillaume
• Primary Examiner(s): Dorvil; Richemond
• Assistant Examiner(s): Borsetti; Greg
• Application Number:
  US11/710,613
• Publication Number:
  US 20070276660A1
• Time in Patent Office: 1,555 Days
• Field of Search: 704/233, 704/E21.002, 704/E21.009, 381/71.1, 381/71.4, 381/71.12
• US Class Current: 704/233
• CPC Class Codes: G10L 21/0208 Noise filtering

Abstract

A method of analyzing time coherence in the noisy signal including the steps of: 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 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. In a data processing apparatus, a method of denoising an original noisy signal, said original noisy signal including a speech component and a noise component, the noise component comprising a transient noise component and a pseudo-steady noise component, the method comprising analyzing time coherence of the sampled noisy signal comprising the steps of:

a) determining a reference signal by processing the original noisy signal by attenuating the speech components more strongly than the noise component, said processing comprising;

a1) applying an adaptive linear prediction algorithm operating on a linear combination of a plurality of samples of the noisy signal, said samples of said noisy signals temporally taken prior to said original noisy signal, to produce a predictive signal; and

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

b) determining probability of speech being absent on the basis of the respective energy levels in the spectral domain of the original noisy signal and of the reference signal; and

c) using said probability of the absence of speech to estimate a noise spectrum and deriving from the original noisy signal a denoised estimate of the speech signal;

wherein the noisy signal is received by a single microphone.

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 is an algorithm of the least mean square (LMS) type.

4. The method of claim 1, in which the linear prediction algorithm 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 (MCRA) type.

7. The method of claim 1, in which step c) further 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.

9. The method of claim 1, wherein said data processing apparatus comprises a hands free apparatus for mobile telephones.