JP2017040752A - Voice determining device, method, and program, and voice signal processor - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide a voice determining device and a voice signal processor for determining presence of interfering voice precisely.SOLUTION: A voice determining device 1 includes: front suppression signal generation part 20 that acquires a frequency domain input signal obtained by converting an input signal from a time domain to a frequency domain, and generates a front suppression signal having a dead angle on the front based on a difference in the acquired frequency domain input signals for each microphone; a coherence calculation part 30 for calculating coherence from input signals obtained from the plurality of microphones; and a determination part 40 for calculating the amount of feature for indicating a relationship between the coherence calculated by the coherence calculation part and the front suppression signal, and determining the presence or absence of interfering voice based on the value of the amount of feature.SELECTED DRAWING: Figure 1

Description

  The present invention relates to a sound determination device, method and program, and a sound signal processing device. For example, a non-target sound other than a target sound (for example, disturbing sound) in a sound process or a speech recognition process in a telephone or a video conference. It can be applied to the determination of the presence or absence.

  In recent years, devices that support various voice processing functions such as voice call functions and voice recognition functions such as smartphones and car navigation systems (hereinafter, these devices are collectively referred to as “voice processing devices”) have become widespread. ing. However, with the widespread use of these voice processing devices, the voice processing devices have come to be used in harsher noise environments than before, such as in crowded streets and in running cars. For this reason, there is an increasing demand for speech processing devices that can maintain call quality and speech recognition performance even in noisy environments.

  When a target sound is extracted and acquired in a conventional speech processing apparatus, processing for suppressing non-target sounds other than the target sound is performed.

  As a conventional speech processing apparatus for suppressing non-target sounds, for example, there is a technique described in Patent Document 1.

  In the device described in Patent Document 1, a delay subtraction process is performed on an input audio signal to form first and second directivity signals having blind spots in first and second predetermined directions, and these two directivities are formed. Get coherence of sex signal. In the apparatus described in Patent Document 1, the acquired coherence is compared with the determination threshold value, and the input voice signal is a section of the target voice arriving from the target direction or other non-target voice section. The gain is set according to the determination result, and the input audio signal is multiplied by the gain to attenuate the non-target audio.

JP 2013-182044 A

  By the way, the components included in the normal non-target sound include, for example, background noise (for example, crowds in the city, driving noise of automobiles, etc.) and disturbing sound (for example, people other than the user of the sound processing device). (Speaking voice). Conventionally, various effective suppression methods have been proposed on the assumption that the background noise has constant frequency characteristics and power. On the other hand, the disturbing voice is a human voice as well as the target voice (voice of the voice processing function user) in addition to non-stationary signal power and frequency characteristics. Therefore, in the conventional speech processing device, when detecting the disturbing speech, it is difficult to determine the presence / absence based on the difference in behavior from the target speech such as background noise. For this reason, when trying to suppress the interfering sound with a conventional sound processing device, the sound quality distortion becomes significant due to excessive suppression processing regardless of the presence or absence of the interfering sound, or the residual component of the interfering sound due to insufficient suppression Therefore, there arises a problem that the voice quality and voice recognition performance do not reach predetermined levels.

  In view of the above problems, a voice determination device, a method and a program, and a voice signal processing device that can accurately determine the presence of a non-target sound (for example, disturbing voice) are desired.

  The speech determination apparatus according to the first aspect of the present invention provides (1) a frequency domain input signal obtained by converting input signals obtained from a plurality of microphones from a time domain to a frequency domain, and the obtained frequency domain input for each microphone. A front suppression signal generation unit that generates a frontal suppression signal having a blind spot in front based on the signal difference; (2) a coherence calculation unit that calculates coherence from input signals obtained from the plurality of microphones; And a determination unit that calculates a feature amount representing a relationship between the coherence calculated by the coherence calculation unit and the front suppression signal, and determines presence / absence of disturbing speech based on the value of the feature amount. And

  The sound determination program according to the second aspect of the present invention provides a computer, (1) obtains a frequency domain input signal obtained by converting input signals obtained from a plurality of microphones from a time domain to a frequency domain, and obtains each of the obtained microphones. A front suppression signal generation unit that generates a frontal suppression signal having a blind spot in front based on a difference between frequency domain input signals; and (2) a coherence calculation unit that calculates coherence from input signals obtained from the plurality of microphones. (3) calculating a feature value representing the relationship between the coherence calculated by the coherence calculation unit and the front suppression signal, and functioning as a determination unit that determines the presence or absence of disturbing speech based on the value of the feature value It is characterized by that.

  According to a third aspect of the present invention, in the determination method for input signals obtained from a plurality of microphones, (1) a front suppression signal generation unit, a coherence calculation unit, and a determination unit are provided, and (2) the front suppression signal generation unit includes: A front side having a blind spot on the front side based on the difference between the obtained frequency domain input signals for each microphone, acquiring a frequency domain input signal obtained by converting input signals obtained from a plurality of microphones from a time domain to a frequency domain Generating a suppression signal, (3) the coherence calculation unit calculates coherence from input signals obtained from the plurality of microphones, (4) the determination unit, the coherence calculated by the coherence calculation unit, A feature amount representing a relationship with the front suppression signal is calculated, and the presence or absence of disturbing speech is determined based on the value of the feature amount.

  According to a fourth aspect of the present invention, in a voice processing apparatus that performs voice processing of input signals obtained from a plurality of microphones, voice processing is performed using the determination result of the voice determination apparatus according to the first aspect of the present invention. .

  ADVANTAGE OF THE INVENTION According to this invention, the audio | voice determination apparatus and audio | voice signal processing apparatus which determine a disturbance audio | voice accurately can be provided.

It is the block diagram shown about the functional structure of the audio | voice determination apparatus which concerns on embodiment. It is explanatory drawing shown about the example of arrangement | positioning of the microphone which concerns on embodiment. It is the figure (the 1) shown about the characteristic of the directional signal applied with the audio | voice determination apparatus which concerns on embodiment. It is the figure (the 2) shown about the characteristic of the directional signal applied with the audio | voice determination apparatus which concerns on embodiment. It is the flowchart (the 1) shown about the example of operation | movement of the audio | voice determination apparatus which concerns on embodiment. It is the flowchart (the 2) shown about the example of operation | movement of the audio | voice determination apparatus which concerns on embodiment.

(A) Main Embodiment Hereinafter, an embodiment of a sound determination device, method and program, and sound signal processing device, method and program according to the present invention will be described in detail with reference to the drawings.

(A-1) Configuration of Embodiment FIG. 1 is a block diagram showing an overall configuration of a voice determination device 1 of this embodiment.

  The voice determination device 1 acquires input signals s1 (n) and s2 (n) from each of the pair of microphones m_1 and m_2 via an AD converter (not shown). Note that n is an index indicating the input order of samples, and is expressed as a positive integer. In the text, it is assumed that the smaller n is the older input sample, and the larger n is the newer input sample.

  The sound determination device 1 determines whether or not a non-target sound is included in the input signal supplemented by the microphones m_1 and m_2, and supplies the determination result to the sound processing device 2. The voice processing device 2 processes the input signal using the determination result supplied from the voice determination device 1. The processing content performed by the audio processing device 2 on the input signal is not limited. The functions and processing contents of the voice processing device 2 are not limited. The voice processing device 2 uses the determination result supplied from the voice determination device 1 for preprocessing of a communication device such as a video conference system or a mobile phone terminal and a voice recognition function, for example. For example, the sound processing device 2 uses the determination result supplied from the sound determination device 1 for the non-target sound (for example, disturbing sound) suppression processing or the like.

  FIG. 2 is an explanatory diagram showing an example of the arrangement of the microphones m_1 and m_2.

  As shown in FIG. 2, in this embodiment, the microphones m_1 and m_2 are such that the plane including the two microphones m_1 and m_2 is perpendicular to the direction in which the target sound arrives (the direction of the target sound source). It is assumed that it is arranged. In the following, as shown in FIG. 2, the arrival direction of the target sound is referred to as the front direction or the front direction when viewed from the position between the two microphones m_1 and m_2. In the following, as shown in FIG. 2, when referring to the right direction, the left direction, and the rear direction, each direction when the arrival direction of the target sound is viewed from the position between the two microphones m_1 and m_2 is shown. It will be explained as a thing. In this embodiment, it is assumed that the target sound comes from the front direction of the microphones m_1 and m_2, and the non-target sound including the disturbing sound comes from the left-right direction (lateral direction).

  The speech determination apparatus 1 includes an FFT unit 10, a front suppression signal generation unit 20, a coherence calculation unit 30, and a determination unit 40.

  The voice determination apparatus 1 may be realized by installing a program (a program including the voice determination program according to the embodiment) in a computer having a processor, a memory, and the like. Specifically, it can be shown using FIG. Note that part or all of the voice determination device 1 may be realized by hardware.

The FFT unit 10 receives input signal sequences s1 and s2 from the microphone m1 and the microphone m2, and performs fast Fourier transform (or discrete Fourier transform) on the input signals s1 and s2. As a result, the input signals s1 and s2 are expressed in the frequency domain. Note that, in performing the fast Fourier transform, the FFT unit 10 includes an analysis frame FRAME1 (K) including predetermined N samples (N is an arbitrary integer) from the input signals s1 (n) and s2 (n). Assume that FRAME2 (K) is configured. An example of configuring FRAME1 from the input signal s1 is shown in the following equation (1). In the following equation (1), K is an index representing the order of frames and is represented by a positive integer. In the following, it is assumed that the smaller the K value, the older the analysis frame, and the larger the K value, the newer the analysis frame. In the following description of the operation, it is assumed that the index representing the latest analysis frame to be analyzed is K unless otherwise specified.
FRAME1 (1) = {s1 (1), s1 (2)... S1 (i),.
FRAME1 (K) = {s1 (N × K + 1), s1 (N × K + 2).., S1 (N × K + i),... S1 (N × K + N)} (1)

  The FFT unit 10 performs a fast Fourier transform process for each analysis frame, thereby performing a frequency domain signal X1 (f, K) obtained by performing a Fourier transform on the analysis frame FRAME1 (K) configured from the input signal s1, and an input signal. A frequency domain signal X2 (f, K) obtained by Fourier transforming the analysis frame FRAME2 (K) configured from s2 is acquired. Note that f is an index representing a frequency. In addition, (f, K) is not a single value, but is composed of m (m is an arbitrary integer) spectral components of a plurality of frequencies f1 to fm as shown in the following equation (2). Shall.

  The FFT unit 10 supplies the frequency domain signals X 1 (f, K) and X 2 (f, K) to the front suppression signal generation unit 20 and the coherence calculation unit 30.

X1 (f, K) is a complex number and is composed of a real part and an imaginary part. The same applies to X2 (f, K) and “N (f, K)” described in the front suppression signal generation unit 20 described later.
X1 (f, K) = {X1 (f1, K), X1 (f2, K),... X1 (fi, K) .., X1 (fm, K)} (2)

  Next, the front suppression signal generation unit 20 will be described.

  The front suppression signal generation unit 20 performs a process of suppressing the signal component in the front direction for each frequency with respect to the signal supplied from the FFT unit 10. In other words, the front suppression signal generation unit 20 functions as a directivity filter that suppresses a component in the front direction.

  For example, as shown in FIG. 3, the front suppression signal generation unit 20 uses an 8-shaped bi-directional filter having a blind spot in the front direction to generate a front direction component from the signal supplied from the FFT unit 10. A directional filter that suppresses the noise is formed.

Specifically, the front suppression signal generation unit 20 is represented by the following equation (3) based on the signals “X1 (f, K)” and “X2 (f, K)” supplied from the FFT unit 10. A calculation is performed to generate a front suppression signal N (f, K) for each frequency. The calculation of the following equation (3) corresponds to a process of forming an 8-shaped bi-directional filter having a blind spot in the front direction as shown in FIG.
N (f, K) = X1 (f, K) -X2 (f, K) (3)

Then, the front suppression signal generation unit 20 calculates an average front suppression signal AVE_N (K) by averaging N (f, K) over all frequencies using the following equation (4).

  Next, the process of the coherence calculation unit 30 will be described.

  The coherence calculator 30 has a strong directivity (for example, as shown in FIG. 4A) in the left direction (first direction) for the frequency domain signals X1 (f, K) and X2 (f, K). A signal processed by a filter of directivity (hereinafter referred to as “directivity signal B1 (f)”) and directivity strong in the right direction (second direction) (for example, as shown in FIG. 4B) A coherence COH (K) based on a signal (hereinafter, referred to as “directional signal B2 (f)”) processed by a filter having a unidirectionality). Note that the directionality of the directivity signal B1 (f) and the directivity signal B2 (f) is an arbitrary direction other than the front direction (however, it is necessary to set different directions for B1 (f) and B2 (f)). There may be a).

  A specific calculation process (for example, a calculation formula) for calculating the coherence COH (K) is not limited. For example, a process similar to that of Patent Document 1 (for example, described in Patent Document 1 ( Since the calculation processing of the formulas (3) to (7) can be applied, details are omitted.

  Next, the process of the determination part 40 is demonstrated.

  The determination unit 40 determines the presence / absence of a non-target sound by using the front suppression signal N (f, K) (average front suppression signal AVE_N (K)) having directivity other than the front and the coherence COH (K). .

  Here, description will be made assuming that the target sound comes from the front direction of the microphones m_1 and m_2, and the non-target sound including the disturbing sound comes from the left-right direction (lateral direction). For example, when the microphones m_1 and m_2 are applied to the microphone portion of the handset of a telephone terminal (for example, a mobile phone terminal), the voice of the speaker (user) as the target sound comes from the front direction of the microphones m_1 and m_2. However, the voice other than the speaker of the telephone terminal comes from the left-right direction (lateral direction).

  Therefore, for example, when “no disturbing voice exists” and “the target sound exists”, the average front suppression signal AVE_N (K) of the front suppression signal N (f, K) has the magnitude of the target sound component. Proportional value. As shown in FIG. 2, the directivity characteristics when generating the average front suppression signal AVE_N (K) (front suppression signal N (f, K)) are “no disturbing speech” and “the target sound exists”. This is because the signal component coming from the front direction is also included. However, as shown in FIG. 2, the directivity characteristic when generating the average front suppression signal AVE_N (K) (front suppression signal N (f, K)) includes a signal component coming from the front direction. Very small compared to the direction gain. In addition, the gain of the front suppression signal N (f, K) when “no disturbing sound exists” and “the target sound exists” is smaller than when the disturbing sound exists.

  The coherence COH (K) can be simply described as a correlation (feature amount) between a signal arriving from the first direction (right direction) and a signal arriving from the second direction (left direction). Therefore, the case where the coherence COH (K) is small is a case where the correlation between the two directivity signals B1 (f) and B2 (f) is small, and conversely, the case where the coherence COH (K) is large is large. In other words. The case where the correlation is small is when the arrival direction of the target sound is greatly deviated to the right or left, or a signal having a clear and regularity such as noise even if there is no deviation. For example, when the microphones m_1 and m_2 are applied to the microphone part of a telephone terminal (for example, a cellular phone terminal), the speaker's voice (target voice) comes from the front and the disturbing voice is other than the front. The tendency to come from is strong. As described above, the coherence COH (K) is a feature amount having a deep relationship with the arrival direction of the input signal. Therefore, the value of coherence COH (K) tends to increase when “no disturbing speech exists” and “the target sound exists”, and when “jamming speech exists”, coherence COH (K ) Tends to be smaller.

  If the behavior of each of the above values is organized by paying attention to the presence or absence of interfering speech, the presence or absence of interfering speech can be determined under the following conditions. In the following, the condition that “no disturbing sound exists” and “the target sound exists” (hereinafter referred to as “first condition”) and the condition that “the disturbing sound exists” (hereinafter referred to as “second sound”). The method for determining the presence / absence of interfering speech will be described for each case.

  In the case of the first condition (“no disturbing sound” and “target sound”), the coherence COH (K) is a relatively large value, and the average front suppression signal AVE_N (K) is The value is proportional to the size of the target sound component.

  On the other hand, in the case of the second condition (when “disturbing speech is present”), the value of coherence COH (K) tends to be a small value, and average front suppression signal AVE_N (K) tends to be a large value.

  Therefore, when the correlation coefficient cor (K) of the average front suppression signal AVE_N (K) and coherence COH (K) is introduced, the relationship between the correlation coefficient cor (K) and the presence or absence of disturbing speech is as follows: Become.

  When no disturbing speech exists, the correlation coefficient cor (K) tends to be a positive value (a value equal to or higher than a predetermined value indicating high correlation). On the other hand, when disturbing speech exists, the correlation coefficient cor (K) tends to be a negative value (a value less than a predetermined value indicating that the correlation is low).

  That is, by introducing the correlation coefficient cor (K) between the average front suppression signal AVE_N (K) and the coherence COH (K), for example, simple processing of determining whether the correlation coefficient cor (K) is positive or negative can be performed. The presence or absence of sound can be determined.

  Accordingly, the determination unit 40 of this embodiment first obtains the correlation coefficient cor (K) and determines the presence or absence of disturbing speech based on the correlation coefficient cor (K).

The specific calculation method used when the determination unit 40 calculates the correlation coefficient cor (K) is not limited. For example, the determination unit 40 uses the following equation (5) to calculate the correlation coefficient. cor (K) may be obtained. In the following equation (5), Cov [AVE_N (K), COH (K)] indicates the covariance between the average front suppression signal AVE_N (K) and the coherence COH (K). In the following equation (5), σN (f, K) represents the standard deviation of the average front suppression signal AVE_N (K). Furthermore, in the following equation (5), σCOH (K) represents a standard deviation of coherence COH (K). When the correlation coefficient cor (K) is obtained by the following equation (5), the standard deviation is obtained using the result of a predetermined number i frames most recently processed for AVE_N (K) and COH (K). Or covariance may be obtained. Specifically, in the process of obtaining the correlation coefficient cor (K) by the following equation (5), for example, i frames (Ki-th frame, K- (i-1) processed most recently) The standard deviations (σN (f, K) and σCOH (K)) and covariances (CON and AVE_N) of the first frame,..., K−1th frame, Kth frame) and covariance ( Cov [AVE_N (K), COH (K)]) may be obtained. In other words, in the process of obtaining the correlation coefficient cor (K), the determination unit 40 obtains the standard deviation and covariance in the following equation (5) using the most recently obtained i AVE_N and COH as samples. You may do it.

  For example, when the correlation coefficient cor (K) is equal to or greater than the threshold Th, the determination unit 40 outputs a value indicating no disturbing voice (for example, “0”), and the correlation coefficient cor (K) is greater than the threshold Th. If it is small, the presence of disturbing sound may be output. In this embodiment, the description will be made assuming that the threshold value Th = 0 is set in accordance with the above-described examination. Therefore, when the correlation coefficient cor (K) is greater than 0 (when the correlation coefficient cor (K) is positive; when cor (K)> 0), the determination unit 40 determines that there is no disturbing voice, When the correlation coefficient cor (K) is less than 0 (when the correlation coefficient cor (K) is 0 or negative; 0 ≧ cor (K)), it is determined that there is disturbing sound.

  Further, the determination unit 40 outputs a signal R (K) indicating the determination result. The format of the signal R (K) is not limited. For example, a value indicating “with disturbing sound” (for example, “1”) or a value indicating “without disturbing sound” (for example, “0”) is used. You may make it output. In this embodiment, the determination unit 40 supplies the signal R (K) to the sound processing device 2. It should be noted that the method by which the determination unit 40 outputs the signal R (K) and the supply destination are not limited.

(A-2) Operation | movement of embodiment Next, operation | movement (determination method of embodiment) of the audio | voice determination apparatus 1 of this embodiment which has the above structures is demonstrated.

  First, the overall operation of the speech determination apparatus 1 will be described with reference to FIG.

  Assume that input signals s1 (n) and s2 (n) for one frame (for one processing unit) are supplied to the FFT unit 10 from each of the microphones m_1 and m_2 via an AD converter (not shown). Then, the FFT unit 10 performs Fourier transform on the analysis frames FRAME1 (K) and FRAME2 (K) based on the input signals s1 (n) and s2 (n) for one frame, and the signal X1 (f, K) and X2 (f, K) are acquired. Then, the signals X1 (f, K) and X2 (f, K) generated by the FFT unit 10 are supplied to the front suppression signal generation unit 20 and the coherence calculation unit 30.

  The front suppression signal generator 20 calculates the front suppression signal N (f, K) based on the supplied X1 (f, K) and X2 (f, K). Then, the front suppression signal generation unit 20 calculates an average front suppression signal AVE_N (K) based on the front suppression signal N (f, K) and supplies the average front suppression signal AVE_N (K) to the determination unit 40.

  On the other hand, the coherence calculation unit 30 generates coherence COH (K) based on the supplied X1 (f, K) and X2 (f, K), and supplies the coherence COH (K) to the determination unit 40.

  The determination unit 40 calculates a correlation coefficient cor (K) based on the average front suppression signal AVE_N (K) and the coherence COH (K), and based on the calculated correlation coefficient cor (K), the presence / absence of disturbing speech And the determination result is output as a signal R (K).

  Next, details of the operation of the determination unit 40 will be described using the flowcharts of FIGS. 5 and 6.

  FIG. 5 is a flowchart illustrating the process in which the determination unit 40 determines the presence or absence of disturbing sound. FIG. 6 is a flowchart showing a part of the processing of the flowchart of FIG. Each time the average front suppression signal AVE_N (K) and coherence COH (K) (data for one frame) are supplied, the determination unit 40 determines the presence or absence of interfering speech by the processing of the flowcharts of FIGS. , Signal R (K) is output.

  When the average front suppression signal AVE_N (K) and the coherence COH (K) are supplied (S101), the determination unit 40 determines the correlation coefficient cor based on the average front suppression signal AVE_N (K) and the coherence COH (K). (K) is calculated (S102).

  Next, the determination unit 40 determines the presence / absence of interfering speech based on the calculated correlation coefficient cor (K) (S103), and generates and outputs a signal R (K) indicating the determination result (S104). .

  Next, a specific example of the determination process performed by the determination unit 40 in step S103 described above will be described with reference to the flowchart of FIG.

  When the determination process is started, the determination unit 40 confirms the value of the correlation coefficient cor (K) (S201), and determines the presence or absence of interfering sound according to the value of the correlation coefficient cor (K).

  Specifically, when the correlation coefficient cor (K) is greater than 0 (when the correlation coefficient cor (K) is a positive value; when cor (K)> 0), the determination unit 40 determines that “interfering voice”. When the correlation coefficient cor (K) is less than 0 (when the correlation coefficient cor (K) is 0 or a negative value; 0 ≧ cor (K)), It is determined that there is a disturbing voice (S203).

(A-3) Effects of Embodiment According to this embodiment, the following effects can be achieved.

  In the voice determination device 1 of this embodiment, the presence / absence of disturbing voice is determined based on the value of the correlation coefficient cor (K). As a result, the sound determination device 1 of this embodiment can accurately determine the presence or absence of interfering sound, so that it is optimal according to the presence or absence of disturbing sound at the determination result supply destination (for example, the sound processing device 2). Voice processing can be realized. That is, by applying the determination result of the audio determination device 1 of this embodiment to the audio processing of the audio processing device 2 (for example, a communication device such as a video conference system or a mobile phone, or preprocessing of the audio recognition function), An improvement in the performance of the processing device 2 (for example, an improvement in the performance of suppressing non-target sounds such as disturbing sounds) can be expected.

(B) Other Embodiments The present invention is not limited to the above-described embodiments, and may include modified embodiments as exemplified below.

  (B-1) In the above embodiment, the sound determination device 1 and the sound processing device 2 have been described as separate components. However, the sound determination device 1 and the sound processing device 2 are constructed as one sound processing device (one device including the sound determination device). It may be.

  (B-2) Although the voice determination device 1 of the above embodiment has been described with respect to an example in which processing is performed based on input signals supplied from two microphones, the voice determination device 1 is supplied from three or more microphones. The determination process may be performed based on the input signal. For example, in the voice determination device 1, based on input signals supplied from three or more microphones, the front suppression signal N (f, K) having a blind spot in the front direction or directivity in a predetermined direction other than the front The directivity signals B1 (f) and B2 (f) may be acquired and the same processing as in the above embodiment may be performed. That is, in the voice determination device 1, the configuration of a microphone for acquiring the front suppression signal N (f, K) and the directivity signals B1 (f) and B2 (f) is not limited.

  (B-3) In the determination unit 40 according to the above-described embodiment, the average front suppression signal AVE_N (K) and the coherence COH are used as the feature amount representing the relationship between the average front suppression signal AVE_N (K) and the coherence COH (K). Although the correlation coefficient cor (K) with (K) is applied, other types of values may be applied as feature quantities. For example, in the determination unit 40, the covariance between the average front suppression signal AVE_N (K) and the coherence COH (K) is used as a feature amount representing the relationship between the average front suppression signal AVE_N (K) and the coherence COH (K). You may make it apply.

  DESCRIPTION OF SYMBOLS 1 ... Voice determination apparatus, 2 ... Speech processing apparatus, 10 ... FFT part, 20 ... Front suppression signal generation part, 30 ... Coherence calculation part, 40 ... Interference sound determination part, m_1, m_2 ... Microphone.

Claims (8)

Obtaining a frequency domain input signal obtained by converting input signals obtained from a plurality of microphones from a time domain to a frequency domain, and based on the obtained difference of the frequency domain input signals for each microphone, frontal suppression having a blind spot in front A front suppression signal generator for generating a signal;
A coherence calculator for calculating coherence from input signals obtained from the plurality of microphones;
A determination unit that calculates a feature amount indicating a relationship between the coherence calculated by the coherence calculation unit and the front suppression signal, and determines the presence or absence of disturbing speech based on the value of the feature amount. A voice determination device.   The speech determination apparatus according to claim 1, wherein the feature amount is a correlation coefficient between the front suppression signal and the coherence.   The speech determination apparatus according to claim 2, wherein the determination unit determines the presence or absence of interfering speech based on the sign of the correlation coefficient as the feature amount.   The speech determination apparatus according to claim 1, wherein the feature amount is a covariance between the front suppression signal and the coherence.   The speech determination apparatus according to claim 2, wherein the determination unit determines the presence or absence of interfering speech based on the sign of covariance as the feature amount. Computer
Obtaining a frequency domain input signal obtained by converting input signals obtained from a plurality of microphones from a time domain to a frequency domain, and based on the obtained difference of the frequency domain input signals for each microphone, frontal suppression having a blind spot in front A front suppression signal generator for generating a signal;
A coherence calculator for calculating coherence from input signals obtained from the plurality of microphones;
Calculating a feature value representing a relationship between the coherence calculated by the coherence calculation unit and the front suppression signal, and functioning as a determination unit that determines the presence or absence of disturbing speech based on the value of the feature value. A voice determination program. In the determination method regarding input signals obtained from a plurality of microphones,
A front suppression signal generation unit, a coherence calculation unit, and a determination unit;
The front suppression signal generation unit obtains a frequency domain input signal obtained by converting input signals obtained from a plurality of microphones from a time domain to a frequency domain, and based on the obtained frequency domain input signal difference for each microphone. Generate a frontal suppression signal with a blind spot in front,
The coherence calculating unit calculates coherence from input signals obtained from the plurality of microphones;
The determination unit calculates a feature amount representing a relationship between the coherence calculated by the coherence calculation unit and the front suppression signal, and determines presence / absence of disturbing speech based on the value of the feature amount. Voice judgment method to do.   6. A voice processing apparatus that performs voice processing of input signals obtained from a plurality of microphones, and performs voice processing using the determination result of the voice determination apparatus according to claim 1. apparatus.

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