Classifications

• • G—PHYSICS
  • G10—MUSICAL INSTRUMENTS; ACOUSTICS
  • G10L—SPEECH ANALYSIS TECHNIQUES OR SPEECH SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING TECHNIQUES; SPEECH OR AUDIO CODING OR DECODING
  • G10L21/00—Speech or voice signal processing techniques to produce another audible or non-audible signal, e.g. visual or tactile, in order to modify its quality or its intelligibility
  • G10L21/02—Speech enhancement, e.g. noise reduction or echo cancellation
  • G10L21/0208—Noise filtering
• • G—PHYSICS
  • G10—MUSICAL INSTRUMENTS; ACOUSTICS
  • G10L—SPEECH ANALYSIS TECHNIQUES OR SPEECH SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING TECHNIQUES; SPEECH OR AUDIO CODING OR DECODING
  • G10L21/00—Speech or voice signal processing techniques to produce another audible or non-audible signal, e.g. visual or tactile, in order to modify its quality or its intelligibility
  • G10L21/02—Speech enhancement, e.g. noise reduction or echo cancellation
  • G10L21/0208—Noise filtering
  • G10L21/0216—Noise filtering characterised by the method used for estimating noise
  • G10L2021/02161—Number of inputs available containing the signal or the noise to be suppressed
  • G10L2021/02165—Two microphones, one receiving mainly the noise signal and the other one mainly the speech signal
• • G—PHYSICS
  • G10—MUSICAL INSTRUMENTS; ACOUSTICS
  • G10L—SPEECH ANALYSIS TECHNIQUES OR SPEECH SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING TECHNIQUES; SPEECH OR AUDIO CODING OR DECODING
  • G10L21/00—Speech or voice signal processing techniques to produce another audible or non-audible signal, e.g. visual or tactile, in order to modify its quality or its intelligibility
  • G10L21/02—Speech enhancement, e.g. noise reduction or echo cancellation
  • G10L21/0208—Noise filtering
  • G10L21/0216—Noise filtering characterised by the method used for estimating noise

Definitions

• the present invention relates to a signal processing, in particular a speech signal in telephony.
• the boom in telecommunications has enabled the general public to benefit from mobile communication tools. It has now become possible and common to telephone from anywhere (of course in the extent of network coverage areas) in environments such as a street, a train station or a vehicle. Nevertheless, such places do not enjoy the calm of a home and the comfort of communication that still offers fixed telephony.
• the annoyance due to the disturbance described as "noise” is generally a source of discomfort and is further accentuated by the dematerialisation of sound recording (the so-called "hands-free” system) which still encourages the emergence of noise due to increasing the distance between the mouth of the speaker and the microphone.
• ANC adaptive noise cancellation
• An input signal x constitutes a useful component and to which is naturally added a noise component, and a noise reference b 2 correlated to the noise component added to the useful signal x, are propagated up to a treatment stage (right part of Figure 1).
• the treatment can be described as follows.
• adaptive Noise Canceller for "Adaptive Noise Canceller" is the filtering of the reference b 2 ( ”) adequately in order to obtain the best estimate of b j (n) (as defined in minimum mean squared error), which brings a reduction in output noise.
• V ⁇ (z) and V2 ⁇ z / respectively represent the Z transforms of vj ( «)
• Equation (3) In the absence of information on the second-order statistics of observations, an alternative to the solution of equation (3) is to perform an adaptive estimation of H. We then choose a parametric model of W in the form, for example, of a finite impulse response (FIR) filter whose coefficients are estimated
• multi-sensor system (called “multidirectional") a priori allows better noise reduction performance than a traditional sound pickup from a single sensor.
• the reference noise b 2 is often mixed with a component from the wanted signal. This is particularly the case when the sensors are spatially close.
• the model of the mixture is now based on two filters h ⁇ iz) and h, 2 ⁇ ⁇ z) which represent the physical (for example acoustic) coupling paths between the source signals and the sensors, as illustrated in Figure 2, representing a mixing model of the input signals X 1 (n) and x 2 (n), coming for example from two respective microphones of a sound acquisition module.
• the signals picked up by the microphones contain mixtures of speech and noise.
• Second-order source separation techniques (without the use of higher-order statistics) make it possible under certain conditions to extract speech from noise with a minimum of damage.
• FIG. 3 illustrates a symmetrical structure of the "backward” type, of denoising in the sense of the reference “Al-Kindi and Dunlop", mentioned above.
• Figure 4 illustrates a symmetrical structure "forward” denoising within the meaning of the reference “Van Gerven and Van Compernolle”, supra.
• the forward source separation structure in particular, has a convergence advantage provided towards the solution but which requires the use of a post-filter causing problems in extracting the output signals. This structure is detailed below.
• FIG. 2 as in FIG. 5, which illustrates the signal mixing model, the filters h xx and / 1 22 are assumed to be "identity" filters, which does not affect the practical use of the model since User speaker of a multi-sensor terminal is expected to stay close to the microphones.
• This hypothesis also reflects the fact that we generally do not have information a priori on the location of source of noise (supposedly point). Note that / ⁇ 12 and / ⁇ 21 are generally non-stationary.
• the forward separation structure of FIG. 6 can be used.
• the present invention improves the situation.
• a device for reducing noise in at least one signal comprising: a structure of the forward type with at least two adaptive filtering channels with noise reduction on two input signals, for delivering two filtered and noise-reduced signals, and at least one post-filter at the output of a channel chosen from among both channels, to reduce distortion on the filtered signal of said selected channel.
• this post-filter comprises an adaptation means according to a comparison involving the input signal of said chosen channel.
• This adaptation means can be constituted by an open loop path or an adaptation feedback.
• the post-filter includes adaptive adaptive filtering feedback, based on a recursive comparison based on the difference between the output signal and the input signal of said selected channel.
• the post-filter comprises an open loop frequency equalizing filter matching means, according to a comparison based on a ratio of power spectral densities, respectively between the filtered signal and the input signal. said chosen channel, brought back to the frequency domain.
• the post-filter comprises adaptive adaptive filter adaptive feedback, according to a recursive comparison based on the difference between the output signal and the input signal, brought back into the frequency domain.
• FIG. 8 illustrates a noise reduction device comprising a two-stage forward structure with post-filtering implementing a means of adataption in the sense of the invention, by open loop frequency equalizer filtering according to the second embodiment. supra,
• FIG. 9 illustrates a noise reduction device comprising a two-stage forward structure with post-filtering implementing adataption feedback within the meaning of the invention, by adaptive frequency matching filtering according to the third embodiment mentioned above,
• FIG. 10 schematically illustrates telecommunication equipment, such as a telephony terminal, comprising a sound acquisition module including two microphones connected to a noise reduction device in the sense of the invention
• FIG. 11 illustrates schematically the steps of a method in the sense of the invention, for the implementation of a treatment according to one of the second or third embodiments mentioned above.
• the noise reduction structure of the forward structure type, comprising: a first input for receiving a first original signal pi (n) , and at least one second input for receiving a second original signal p 2 (n).
• the first and second signals have two respective substantially correlated noise versions.
• the structure further comprises:
• a first subtracter Ss 1 between the first signal and the second filtered signal for delivering a third signal ui (n), the third signal being of reduced noise and corresponding to the first signal to which the second filtered signal is subtracted,
• the forward structure further comprises, in the example shown in FIGS. 7 to 9:
• the aforementioned first post-filter at least, comprises an adaptation means according to a comparison involving the first signal pi (n) and: the fifth signal si (n) in the first signal (FIG. 7) and third (FIG. 9) embodiments, or the third signal U 1 (n) in the second embodiment (FIG. 8), as will be seen below.
• Two possible approaches, within the meaning of the invention, are presented below for the implementation of the post-filter of the signal path p ⁇ (").
• the first possible approach is based on a direct calculation of gain in the time domain, corresponding to a convergent theoretical post-filter.
• a frequency domain calculation is preferred.
• the filter w ft acts as a time equalizer, at each iteration n, of the result of the processing of the stage which precedes it, that is to say of the original forward source separation structure.
• the filter vt> 2 i is updated only during the phases of non-vocal activity and the equalizer filter w ft is updated only during periods of voice activity.
• Such an embodiment therefore ensures equalization in amplitude of the acoustic channel while preserving the same phase as the original signal.
• a voice activity detection module DAV (FIG. 11) is advantageously used to estimate a representative quantity of the noise during the non-activity phases and a representative quantity of the useful signal during the activity phases.
• a device of the state of the art such as a threshold detector.
• the adaptive filter w p must be long, and its convergence is disturbed by the presence of noise superimposed on the speech in the signal p ⁇ (n). It is therefore considered that, in practice, this temporal computation approach gives insufficient performance, contrary to the approach based on the frequency calculation described hereinafter.
• the second approach in the sense of the invention is based on a gain calculation in the frequency domain.
• the second embodiment of the invention is directed to the direct gain calculation in the frequency domain, corresponding to a theoretical post-filter.
• a frequency adaptive algorithm is advantageously used, for example of the FLMS type (for "Frequency-domain Least Mean Squares") for calculating the post-filter.
• An algorithm of this type is described in particular in:
• FIG. 8 shows a forward structure with calculation of the open loop frequency equalizer filter post-filter for the implementation of the invention according to the second aforementioned embodiment.
• the frequency gain G ( ⁇ , k) is calculated which is used to equalize in amplitude (and not in phase) the output signal of the separation structure W 1 (n). This gain is calculated from the unbalanced output signal and the mixing signal. It aims to restore, for each spectral component of the output signal, the same amplitude as the corresponding amplitude of the component of the speech signal present in the mixing signal p ⁇ (n).
• the power spectral densities of the signals W 1 (n) and p ⁇ (n) are estimated here by means of a recursive calculation formula of the first order from the calculation of their fast Fourier transforms (or "FFT").
• the calculation of the frequency gain is realized by the following formula:
• the two quantities DSP _signal and DSP _hw represent the power spectral densities estimated from the noisy original signal p ⁇ (n) and, respectively, from the noise-free filtered signal W 1 Oi) on a window of several samples (or " frame "k).
• the power spectral density of the original signal is calculated during the periods of speech activity by subtracting the power spectral density of the noise, which is estimated during periods of non-speech activity, with the spectral power density of the signal. mixing mixture W 1 (n). The property of the intermittency of the speech signal is therefore exploited to estimate the different power densities of the structure.
• the speech signal at the output of this structure is recovered after the modification of each frequency component of the signal W 1 U) by the frequency gain G ( ⁇ , k).
• This signal is finally restored in the time domain following an inverse Fourier transform and a conventional reconstruction, for example of the "overlap-save” type described in particular in the reference Ferrara (1980) given previously.
• the good estimate of the signal at the output of this structure is based on the good estimation of the speech signal (calculation of its power spectral density).
• the mixing signal can advantageously be delayed by a delay D (module z ⁇ D of Figures 8 and 9). It is therefore preferable to ensure the correct setting of the delay parameter D for the proper functioning of this structure within the meaning of the invention.
• this parameter D can be set to half the size of the impulse response of the post-filter.
• the third embodiment is described below with reference to FIG. 9, presenting a forward structure with calculation of the post-filter, by adaptive frequency filtering.
• This embodiment is based on the use of an adaptive algorithm for updating the coefficients of gain G ⁇ , k), calculated in the frequency domain.
• the signals being sampled in successive frames, for each signal frame k, an equation of the following type is provided:
• G ( ⁇ , k) G ( ⁇ , k-1) + ⁇ ( ⁇ , k) E ( ⁇ , k) U ⁇ ( ⁇ , k), where:
• G ( ⁇ , k-1) is the calculated gain for a frame k-1, preceding the current frame k,
• the calculation of the adaptation step ⁇ ( ⁇ , fc), at each frame, is typically performed according to a function which follows the rules and conventional principles of noise reduction. It can be a ratio estimate of respective power spectral densities of useful signal and noise. More particularly, this function is based on the calculation of the signal-to-noise ratio components of each frequency line.
• the Wiener function is used for calculating the pitch ⁇ ( ⁇ , k) as follows:
• RSB io ( ⁇ , k) 'k) ⁇ + RSB pn MkY (10)
• a priori which is defined by the ratio between the estimate of the spectral density of power of the noise-cleaned speech signal and the estimated power spectral density of the noise. This signal-to-noise ratio is therefore given by a formula of the type:
• DSP_noise ( ⁇ , k) ⁇ DSP_noise ( ⁇ , k) ⁇
• a variable adaptation step as a function of the signal-to-noise ratio as defined in equation (10) is advantageous because it allows a robust convergence of the adaptive frequency filter and also enables it to correct the signal distortion. of speech.
• the third embodiment proved to be the most robust to inaccuracies in the calculations of the spectral power densities of all the signals involved in the calculation of the filter.
• this third embodiment makes it possible to recover a signal close to the initial signal, which has moreover been confirmed by subjective listening.
• the invention aimed at denoising the speech signal using the forward source separation structure, allows the calculation of the theoretical post-filter regardless of the nature of the post-filter.
• the embodiments presented above make it possible to correct the disadvantages of the forward structure which produces a distortion of the output speech signal if it is not followed by the post-filter.
• the present invention also aims at a sound acquisition module, in particular for a telecommunication equipment (for example a fixed or mobile telephony apparatus) as represented in FIG. 10.
• the sound acquisition module comprises at least:
• a microphone MIC1 for acquiring a signal comprising a useful component and a noise component
• a microphone MIC2 for acquiring a noise reference substantially correlated with the noise component of the input signal
• a FW noise reduction device for supplying a useful signal s u, free from noise and distortion.
• the signal comprising the useful component is applied as an input signal of the channel comprising adaptive post-filtering within the meaning of the invention, and the noise reference is applied as an input signal in the other channel. of the forward structure of the noise reduction device.
• the two signals thus acquired (that including the aforementioned noise component and that corresponding to the noise reference) comprise respective substantially correlated versions of noise.
• the present invention also aims at a noise reduction method in at least one signal, in which a forward structure is provided at least two adaptive noise reduction filter channels W 12 (z), W 21 (z) on two input signals
• a post-filtering is applied with an adaptation means according to a comparison involving the input signal p ⁇ (n) of said chosen channel, to reduce a distortion on the filtered signal M 1 ⁇ n) of this chosen channel.
• FIG. 11 shows the process steps for the second and for the third embodiments described above.
• the DSP power spectral densities (step S101) for evaluating the signal-to-noise ratio (step S102) are calculated and hence the gain G ( ⁇ , k) (step S103).
• a frequency gain G ( ⁇ , k) (step S103) is calculated by exploiting the aforementioned signal-to-noise ratio and, more particularly, the ratio of the spectral densities of DSP powers. respectively.
• step SlOl for calculating the spectral densities of DSP powers, the original input signal p ⁇ (n) and the filtered signal W 1 (W) are brought back to the frequency domain.
• a delay D is applied to the original input signal p ⁇ (n) (step S104), and then the delayed signal is returned to the frequency domain by applying an FFT (step S 105).
• the filtered, noise-free signal W 1 (z) is also returned to the frequency domain by applying an FFT (step S106).
• a processor of a noise reduction device can implement the steps of the method.
• the present invention also provides a computer program, intended to be executed by such a processor, and including instructions for the implementation of the method.
• Figure 11 can illustrate the flowchart of such a computer program.
• the present invention is not limited to the embodiment described above by way of example; it extends to other variants.
• the forward structures of FIGS. 7 to 9 it will be understood that it is possible to provide a forward structure comprising more than two channels and / or more than one adaptive post-filtering in the sense of the invention.
• the post-filtering w P 2 (z) on the noise reference channel of FIGS. 7 to 9 is not necessary for the implementation of the invention and could be omitted.

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• Engineering & Computer Science (AREA)
• Computational Linguistics (AREA)
• Quality & Reliability (AREA)
• Signal Processing (AREA)
• Health & Medical Sciences (AREA)
• Audiology, Speech & Language Pathology (AREA)
• Human Computer Interaction (AREA)
• Physics & Mathematics (AREA)
• Acoustics & Sound (AREA)
• Multimedia (AREA)
• Soundproofing, Sound Blocking, And Sound Damping (AREA)
• Filters That Use Time-Delay Elements (AREA)

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• 2007
  • 2007-09-26 WO PCT/FR2007/052010 patent/WO2008037925A1/fr active Application Filing
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