EP2530673B1 - Equipement audio comprenant des moyens de débruitage d'un signal de parole par filtrage à délai fractionnaire - Google Patents
Equipement audio comprenant des moyens de débruitage d'un signal de parole par filtrage à délai fractionnaire Download PDFInfo
- Publication number
- EP2530673B1 EP2530673B1 EP12170407.6A EP12170407A EP2530673B1 EP 2530673 B1 EP2530673 B1 EP 2530673B1 EP 12170407 A EP12170407 A EP 12170407A EP 2530673 B1 EP2530673 B1 EP 2530673B1
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- Prior art keywords
- speech
- signal
- filter
- equipment
- noise
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Images
Classifications
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- 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
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- 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
Definitions
- microphones include one or more microphones (“microphones”) sensitive, capturing not only the voice of the user, but also the surrounding noise, noise that is a disruptive element that can go in some cases to make unintelligible the speaker's words . It is the same if one wants to implement speech recognition techniques, because it is very difficult to perform a form recognition on words embedded in a high noise level.
- the device is a headset type microphone / headset combined used for communication functions such as "hands-free" telephony functions, in addition to listening to a source audio (music for example) from a device to which the headphones are connected.
- the headset can be used in a noisy environment (metro, busy street, train, etc.), so that the microphone will not only pick up the word of the wearer of the helmet, but also the noise surrounding.
- the wearer is certainly protected from this noise by the helmet, especially if it is a model with closed earphones isolating the ear from the outside, and even more if the headset is provided with an "active control of noise”.
- the distant speaker (the one at the other end of the communication channel) will suffer from the noise picked up by the microphone and being superimposed and interfere with the speech signal of the near speaker (the helmet wearer).
- certain speech formers essential to the understanding of the voice are often embedded in noise components commonly encountered in the usual environments.
- the invention relates more particularly to denoising techniques using several microphones, usually two microphones, to judiciously combine the signals picked up simultaneously by these microphones in order to isolate the useful speech components of the noise noise components.
- this technique has the disadvantage of requiring two remote microphones, the efficiency being even higher than the two microphones are remote. Therefore, this technique is not applicable to a device in which the two microphones are close together, for example two microphones incorporated in the facade of a car radio, or two microphones that would be arranged on one of the shells an earphone.
- the invention proposes audio equipment of the general type disclosed by the US 2008/0280653 A1 above, that is to say comprising: a set of two microphonic sensors able to collect the speech of the user of the equipment and to deliver respective noisy speech signals; means for sampling the speech signals delivered by the microphone sensors; and means for denoising a speech signal, receiving as input the samples of the speech signals delivered by the two microphonic sensors, and outputting a speech signal that is not representative of the speech transmitted by the user of the equipment .
- the adaptive filter is a LMS mean least squares linear prediction algorithm filter.
- the equipment comprises a video camera directed towards the user of the equipment and able to capture an image thereof
- the voice activity detection means comprise suitable video analysis means. analyzing the image produced by the camera and responding in response to said presence or absence of speech signal by said user.
- the equipment may in particular be a headset of the combined microphone / headset type, comprising: headphones each comprising a sound reproduction transducer of an audio signal housed in a shell provided with a circumaural pad; said two microphone sensors, arranged on the shell of one of the earphones; and said physiological sensor, incorporated in the pad of one of the earphones and placed in a region thereof able to come into contact with the cheek or temple of the wearer of the helmet.
- These two microphonic sensors are preferably aligned in a linear array in a main direction directed towards the mouth of the user of the equipment.
- the Figure 1 schematically illustrates, in block form, the various functions implemented by the invention.
- the signal that is desired to be denoised originates from a network of microphone sensors which, in the minimum configuration illustrated, may simply be an array of two sensors arranged in a predetermined configuration, each sensor consisting of a corresponding respective microphone 10 , 12.
- the invention may, however, be generalized to a network of more than two microphone sensors, and / or to microphonic sensors, each sensor of which is constituted by a more complex structure than a simple microphone, for example a combination of several microphones and / or or other speech sensors.
- the microphones 10, 12 are microphones that pick up the signal emitted by the useful signal source (the speech signal from the speaker), and the difference in position between the two microphones induces a set of phase shifts and amplitude variations in the microphone. recording the signals emitted by the useful signal source.
- the useful signal source the speech signal from the speaker
- the two microphones 10, 12 are omnidirectional microphones placed a few centimeters apart from each other on the ceiling of a car interior, on the front of a car radio or in an appropriate location on the car. dashboard, or on the shell of one of the headphones headphones, etc.
- This noise reduction is effected by means of an algorithm seeking the transfer function between one of the microphones (for example the microphone 10) and the other microphone (the microphone 12) by means of an adaptive combiner 14 setting A predictive filter 16 of LMS ( Least Mean Squares ) type is used.
- the output of the filter 16 is subtracted at 18 from the signal of the microphone 10 to give a signal S de-noised, applied back to the filter 16 to allow its iterative adaptation as a function of the prediction error. It is thus possible to predict from the signal picked up by the microphone 12 the noise component contained in the signal picked up by the microphone 10 (the transfer function identifying the noise transfer).
- the adaptive search of the transfer function between the two microphones is performed only during the speech-free phases. For this, the iterative adaptation of the filter 16 is activated only when a voice activity detector VAD ( Voice Activity Detector ) 20 controlled by a sensor 22 indicates that the near speaker is not speaking.
- VAD Voice Activity Detector
- the adaptive combiner 14 seeks to optimize the transfer function between the two microphones 10 and 12 so as to reduce the noise component (closed position of the switch 24, as shown in the figure); on the other hand, in the presence of a speech signal confirmed by the voice activity detector 20, the adaptive combiner 14 freezes the parameters of the filter 16 to the value at which they were just before the speech was detected (opening of the switch 24), which avoids any degradation of the speech signal of the nearby speaker.
- the filtering of the adaptive combiner 14 is a fractional delay filtering, that is to say that it makes it possible to apply a filtering between the signals picked up by the two microphones taking into account the a delay less than the duration of a sample digitizing signals.
- the interval or offset between two samples corresponds temporally to a duration of Te second.
- the Figure 3a gives a graphic representation of this function.
- MicAvant (n) and MicRear (n) being the respective values of the signals from the microphonic sensors 10 and 12.
- the estimation of ⁇ takes place directly, by the minimization of the error e ( n ) above, without there being need to estimate separately ⁇ and F.
- L being the length of the filter.
- the prediction of the filter H gives a fractional delay filter which, ideally and in the absence of speech, cancels the noise of the microphone 10 with reference to the microphone 12 (as indicated above, during speech however, the filter is frozen to prevent any degradation of local speech).
- the Figure 4 illustrates an example of acoustic response between the two microphones, in the form of a characteristic giving the amplitude A as a function of the coefficients k of the filter F.
- the different sound reflections that may occur depending on the environment, for example on the windows or other walls of a car interior, create visible peaks on this acoustic response characteristic.
- the Figure 5 illustrates an example of the result of the convolution G X F of the two filters G (cardinal sinus response) and F (environment of use), in the form of a characteristic giving the amplitude A as a function of the coefficients k of the convoluted filter.
- the estimate ⁇ can be calculated by an iterative LMS algorithm seeking to minimize the error y (n) - ⁇ X x ( n ) to converge towards the optimal filter.
- the voice activity detector is here preferably a "perfect” detector, that is to say it delivers a binary signal (absence vs. presence of speech). It is thus distinguished from most voice activity detectors used in known denoising systems, which deliver only a probability of presence of variable speech between 0 and 100% continuously or in successive steps. With such detectors based only on the probability of speech, false detections can be important in noisy environments. To be “perfect”, the voice activity detector can not rely solely on the signal picked up by the microphones; it must have additional information to discriminate the speech and silence phases of the next speaker.
- a first example of such a detector is illustrated by the Figure 6 , where the voice activity detector 20 operates in response to the signal produced by a camera.
- This camera is for example a camera 26 installed in the passenger compartment of a motor vehicle, and oriented so that its field of view 28 encompasses in all circumstances the driver's head 30, considered as the close speaker.
- the signal delivered by the camera 26 is analyzed to determine from the movement of the mouth and lips whether the speaker speaks or not.
- Video data is added to conventional audio data to improve speech enhancement .
- This treatment may be used in the context of the present invention to distinguish between the speech phases and the silence phases of the speaker.
- the advantage of this image analysis technique is to have complementary information completely independent of the acoustic noise environment.
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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)
- Circuit For Audible Band Transducer (AREA)
Applications Claiming Priority (1)
Application Number | Priority Date | Filing Date | Title |
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FR1154825A FR2976111B1 (fr) | 2011-06-01 | 2011-06-01 | Equipement audio comprenant des moyens de debruitage d'un signal de parole par filtrage a delai fractionnaire, notamment pour un systeme de telephonie "mains libres" |
Publications (2)
Publication Number | Publication Date |
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EP2530673A1 EP2530673A1 (fr) | 2012-12-05 |
EP2530673B1 true EP2530673B1 (fr) | 2013-07-10 |
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Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
EP12170407.6A Active EP2530673B1 (fr) | 2011-06-01 | 2012-06-01 | Equipement audio comprenant des moyens de débruitage d'un signal de parole par filtrage à délai fractionnaire |
Country Status (6)
Country | Link |
---|---|
US (1) | US8682658B2 (zh) |
EP (1) | EP2530673B1 (zh) |
JP (1) | JP6150988B2 (zh) |
CN (1) | CN103002170B (zh) |
ES (1) | ES2430121T3 (zh) |
FR (1) | FR2976111B1 (zh) |
Cited By (1)
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2011
- 2011-06-01 FR FR1154825A patent/FR2976111B1/fr not_active Expired - Fee Related
-
2012
- 2012-05-18 US US13/475,431 patent/US8682658B2/en active Active
- 2012-06-01 ES ES12170407T patent/ES2430121T3/es active Active
- 2012-06-01 CN CN201210179601.4A patent/CN103002170B/zh active Active
- 2012-06-01 EP EP12170407.6A patent/EP2530673B1/fr active Active
- 2012-06-01 JP JP2012125653A patent/JP6150988B2/ja active Active
Cited By (2)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN106157963A (zh) * | 2015-04-08 | 2016-11-23 | 广州质音通讯技术有限公司 | 一种音频信号的降噪处理方法和装置及电子设备 |
CN106157963B (zh) * | 2015-04-08 | 2019-10-15 | 质音通讯科技(深圳)有限公司 | 一种音频信号的降噪处理方法和装置及电子设备 |
Also Published As
Publication number | Publication date |
---|---|
US8682658B2 (en) | 2014-03-25 |
FR2976111B1 (fr) | 2013-07-05 |
FR2976111A1 (fr) | 2012-12-07 |
US20120310637A1 (en) | 2012-12-06 |
CN103002170B (zh) | 2016-01-06 |
JP2012253771A (ja) | 2012-12-20 |
JP6150988B2 (ja) | 2017-06-21 |
ES2430121T3 (es) | 2013-11-19 |
EP2530673A1 (fr) | 2012-12-05 |
CN103002170A (zh) | 2013-03-27 |
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