JP2002300687A - Electronic apparatus - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide an electronic apparatus which realizes a satisfactory noise suppressing function and voice switch function. SOLUTION: The electronic apparatus comprises a voice switch for inserting a loss corresponding to a signal attenuation A in a transmitted or received signal and a noise canceler which detects voice components from the transmitted or received signal, computes a signal attenuation B and compares the attenuation A with the attenuation B to obtain an adjusted final signal attenuation C for suppressing noise.

Description

DETAILED DESCRIPTION OF THE INVENTION

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to an electronic device such as a portable telephone for handling transmission and reception of audio signals.

[0002]

2. Description of the Related Art In a communication system for transmitting and receiving voice such as a mobile phone, a voice switch is mounted on an electronic device (a mobile phone or the like) constituting the communication system in order to prevent howling or the like.

[0003] A voice switch constantly inserts a LOSS into a transmission / reception signal loop, and imposes a predetermined signal reduction amount on either a reception signal or a transmission signal.

[0004] In general, a setting is made so that LOSS is inserted into a transmission signal when only reception is performed and into a reception signal when transmission is only performed. At the time of a so-called double talk or a non-talking state, for example, a setting is made so that a LOSS is inserted on the transmitting side.

[0005] In an electronic device such as a portable telephone for performing voice communication, a voice coding system such as a CELP (Code Excited Linear Prediction) system is used.

When such a device is used in an environment with a large amount of background noise, the background noise is taken in and coded, and the intelligibility of speech is reduced. For this reason, a technology (noise canceller) for removing or suppressing background noise so as to approach a signal containing only speech and performing speech coding has been studied, and has been mounted on electronic devices.

[0007]

As described above, since the voice switch and the noise canceller have different purposes, respectively, electronic devices equipped with both operate independently to exhibit their functions. .

[0008] Therefore, there is a problem that when both of the functions reduce the signal in the same signal system (for example, the transmission system), the signal is reduced more than necessary for both functions.

The voice detection function and the signal reduction function are common functions. Accordingly, a redundant area exists in signal processing.

The present invention has been made in consideration of the above points, and has as its object to provide an electronic apparatus in which a sound signal processing when a noise canceller and a voice switch are provided is improved.

[0011]

SUMMARY OF THE INVENTION The present invention provides a voice switch for inserting a LOSS of a signal reduction amount (A) into a transmission signal or a reception signal; a signal for detecting noise from the transmission signal or the reception signal and suppressing noise. Calculate the reduction (B),
An electronic apparatus comprising: a noise canceller that performs noise suppression with a final signal reduction amount (C) adjusted by comparing the signal reduction amount (A) and the signal reduction amount (B).

That is, without simply adding the signal reduction amount (A) by the voice switch and the signal reduction amount (B) by the noise canceller, the two are compared to determine an appropriate signal attenuation amount.

In general, since the noise canceller operates to perform finer noise reduction (the time variation of the signal attenuation is small), the signal inserted into the transmission / reception system based on the signal reduction (B) of the noise canceller is used as a reference. It is preferred to determine the amount of reduction.

However, from the viewpoint of howling prevention, a certain amount of signal reduction needs to be included in any of the transmission / reception systems.

Therefore, the signal reduction amount (B) of the noise canceller is adopted as a reference of the signal reduction amount, and the upper limit (absolute value lower limit) of the signal reduction amount is set as the signal reduction amount (A) of the voice switch. preferable.

That is, it can be achieved by adjusting the signal reduction amount (B) of the noise canceller to be equal to or less than the signal reduction amount (A) of the voice switch.

The voice switch LOSS is a transmission system,
It is inserted into any of the receiving systems, but the judgment is
It depends on which of the receiving systems has the audio signal.
There are various methods for this determination, and there is no particular limitation.

However, since the noise canceller also determines the presence / absence of an audio signal, the use of this result makes it possible to omit the unique voice signal presence / absence detection processing in the voice switch.

The present invention comprises: a noise canceller for detecting a voice from a transmission signal or a reception signal to suppress noise; and a voice switch for receiving a result of the voice detection in the noise canceller and inserting LOSS into the transmission signal or the reception signal. An electronic device characterized by the above is also provided.

As the noise canceller used in the present invention, various methods such as a noise suppression method in a time domain and a noise suppression method in a frequency domain can be adopted.

For example, in Japanese Patent No. 2995737, an input signal is divided into frames of a predetermined period, noise / speech is determined for each frame, and when a noise frame is determined, a gain value for each band is set to a minimum. However, there is disclosed a method of setting a gain value exceeding that when an audio frame is determined and performing noise suppression, and this method can also be used.

A noise suppression method for dividing an input signal into frames in a predetermined time unit, dividing the divided frames into predetermined frequency bands, and performing noise suppression processing for each of the divided bands. : An audio frame determining step of determining whether the frame is a noise frame or an audio frame; a band-specific gain determining step of setting a band-specific gain value of each frame based on the result of the audio frame determining step; A signal generation step of generating a noise-suppressed output signal by reconstructing a frame after performing noise suppression for each band using the gain value for each band determined in the band gain determination step, In the separate gain determination step, the gain value for each band when the determination target frame is determined to be an audio frame is determined. It is also possible to employ a noise canceller, characterized in that the target frame is set in the band-specific gain value to be taken per-band gain value smaller than the value when it is determined that the noise frame.

In this method, noise in a band that does not include a sound component in a sound frame is sufficiently suppressed, and good noise reduction can be performed. That is, not only is the band-specific gain value for noise suppression determined separately for a voice frame and a noise frame, but the minimum gain value for each band of a voice frame is greater than the minimum gain value for each band of a noise frame. By setting to be smaller, the audibility of the audio signal after noise suppression is improved.

Even if a frame is determined to be an audio frame, not all bands contain audio components. For a band in which it is estimated that the audio component in the frame determined to be an audio frame is not included (or the audio component is small), a gain smaller than the band-specific gain value of the noise frame is set and the audio in the audio frame By making the band containing the component stand out, a good audibility can be obtained.

That is, the gain value for each band of the band in which it is estimated that the speech component is not included in the frame determined to be the speech frame to be determined is determined to be the noise frame. By setting the gain value for each band so as to take a value smaller than the gain value for each band, the band including the audio component in the audio frame can be made more prominent, and as a result, noise suppression with good audibility can be achieved. The obtained output signal can be obtained.

In the noise frame, a constant gain value may be set for each band, or it may be set to change based on the difference between the power for each band and the noise power.

Also, with respect to the voice frame, the gain value for each band is set so as to increase as the index based on the difference between the power for each band and the noise power increases. Is also possible. A function that decreases continuously may be employed.

In such a noise suppression method, there is a step of updating the estimated value of the noise power as a step before determining the above-described gain for each band. This noise estimate is
It is updated under a predetermined condition.
The update method disclosed in the noise suppression method disclosed in No. 0 can be adopted.

This updating method uses the SNR (log value of signal energy / noise energy) for each band of each frame.
The voice metric, which is the sum of the weighted values, is used, and the deviation for each band (log value of signal energy−log value of average value of past signal energy)
Is a technique for updating a noise estimation value using a spectrum deviation that is a sum of absolute values of the noises. If the spectrum deviation falls below a threshold for a predetermined time (for example, one second), the estimated noise value is updated. You.

Also, instead of using the value of the spectral deviation as it is for determination, the total deviation of the difference between the band power and the noise power between the previous frame and the previous frame is normalized by the average value. By determining the noise section at this time, a method can be adopted in which noise having a large inter-frame variation compared to the above method can be recognized as noise.

That is, a significant value for each band in which a difference between the power for each band and the estimated noise power value for each band is weighted in a predetermined manner.
(suby) The sum of the difference between the current frame and the previous frame (s
um) is the ratio (r) normalized by the average value (sum_average)
Is a method for determining whether or not the current frame is a noise frame based on

As described above, the significant value for each band with respect to the past frame
Using the deviation of (suby) and normalizing the deviation with the average value of the total deviation value as the basis for the determination, it is possible to mitigate the variation for each frame. Can be. Therefore, it is possible to satisfactorily recognize noise having large inter-frame variations as noise.

More specifically, a frame dividing step of dividing a transmission input signal into frames in a predetermined time unit; a frequency band dividing step of dividing each frame into a plurality of frequency bands; Calculating a power for each band (channel_power); calculating a difference (tmp) between a noise power estimation value for each band (noise_power) and the power for each band (chennel_power) for each frequency band; (tmp)
A significant value calculating step of calculating a significant value (y) obtained by adding a significant value (suby) for each band obtained by performing a predetermined weighting on a predetermined condition; and between a current frame and a previous frame, Calculating the sum of the absolute values (sum) of the differences of the significant values (suby) of the respective bands for the frequency band of; and calculating the average value (sum_average) of the sum of the absolute values (sum); A significant value normalizing step of calculating a ratio (r) obtained by normalizing the sum of values (sum) by the average value (sum_average) of the sum of absolute values.

Updating the noise power estimate has the following two steps.

That is, when the significant value (y) falls below a predetermined threshold value, the current frame is determined to be a noise frame, and the first noise power estimation value for updating the noise power estimation value (noise_power) for each band is determined. Updating the value; the ratio
When (r) continuously falls below a predetermined threshold for a predetermined period, the current frame is determined to be a noise frame, and the second noise power estimation value for updating the noise power estimation value for each band (noise_power) Update step.

The first noise power estimation value updating step is a case where noise estimation is performed satisfactorily and the frame is determined to be a noise frame by a significant value determination. The second noise power estimation value updating step includes: Even if a significant value varies between frames and a good noise value cannot be determined with a significant value, forced updating can be performed.

As the average value used for normalization, an estimated value obtained by using leak integration of the sum of absolute values (sum) can be used. Further, it is also possible to use an estimated value of the average value (sum_average) obtained by using leak integration of a standard deviation of the sum of absolute values (sum).

In the above-described gain setting for each band, the gain value for each band is determined by using a different function between the case of a voice frame and the case of a noise frame. Basically, it is calculated based on the difference between the power for each band and the noise power for each band (difference in logarithm: SNR). That is, a band having a large SNR in a voice frame is presumed to be a band containing a voice component.
The gain value of the band is set to a large value, the band having a small SNR is estimated to contain no voice component, and the gain value is set to a small value.

Incidentally, noise (Background Noise) is generally assumed to be stationary, but may fluctuate outdoors. In particular, the energy of noise generated when a vehicle passes by increases as the vehicle approaches. If the transmitted voice is input in this state, the suppressed voice may be distorted because the energy difference between the voice and the noise is small. Also, when the spectral shape of the noise is similar to the spectral shape of the voice, the suppression of the noise based on the noise energy makes it easier to interfere with the voice spectrum, so that the suppressed voice is distorted. Even if the noise energy fluctuates, S
It is also possible to suppress such an effect by adjusting the variable for determining the gain value while using the NR as a basis.

In the above-mentioned adjustment, a noise power estimating step of obtaining a signal power for each frequency band and estimating a noise power for each band based on the band power when determining the gain value for each band; A minimum value detecting step of detecting a minimum value of power over at least one of the band power and the band-specific noise power over a plurality of frame periods; and detecting the band power and the minimum value detecting step for each of the frequency bands. This can be performed by determining the noise suppression amount for each frequency band based on the difference obtained from the band-specific minimum value determining step for obtaining the difference from the obtained band-specific minimum value.

Further, using an adjustment value for generating an adjustment value common to different bands for each frame, a difference between a value obtained by adding the minimum value for each band and the adjustment value and the band power is obtained for each frequency band. It is also possible to determine the amount of noise suppression for each frequency band based on this difference.

In the noise section, an adjustment value common to the bands is determined based on the difference between the average value between the minimum values for the respective bands and the average value between the noise powers for the respective bands; Can be obtained by determining an adjustment value common to bands based on a difference between a minimum value among a plurality of band powers in one frame and a maximum value among a plurality of band-specific minimum values.

In the determination of a speech frame and a noise frame, a noise power estimating step of obtaining signal power for each frequency band and estimating noise power for each band based on the band power; Comparing the difference between the noise power and the band power for each band and comparing the difference for each band with a predetermined threshold value; a plurality of adjacent bands among the differences for each band arranged in frequency order The difference between the bands is determined to exceed the threshold value, the band-by-band difference is weighted by a predetermined weight, and then added to each other; And a determining step of determining whether the input signal is a voice section or a noise section based on the added value.

In the adding step, the difference for each band can be weighted so that the weight decreases as the frequency increases. In the determining step, the voice of the input signal is determined based on the added value. Section or
It is possible to determine whether it is a noise section or a transition section which is an intermediate area between both sections.

The present invention as described above uses ACELP, EVR
The present invention can be applied to an electronic device such as a mobile phone adopting a digital voice coding method using various voice coding methods such as C, EFR, and AMR. That is, in an electronic device having an audio signal input unit (a direct input unit such as a microphone or a signal transmitted from an electronic file or the like) and an audio encoding unit, the audio signal of the audio signal input unit is received, and An electronic apparatus includes a noise canceller that supplies a signal whose noise has been suppressed by the noise suppression method to a speech encoding unit, and the above-described voice switch.

The voice switch and the noise canceller can be executed by signal processing in the DSP in the same manner as, for example, speech coding.

[0047]

DESCRIPTION OF THE PREFERRED EMBODIMENTS Embodiments of the present invention will be described.

FIG. 1 is a schematic block diagram of an electronic apparatus showing an embodiment of the present invention.

The reception signal (1) is supplied to an audio output device (3) such as a speaker via a reception signal amplifier (2).
An input signal from a voice input device (4) such as a microphone is transmitted as a transmission signal (9) via a noise canceller NC (5).

The voice switch VS (6) detects the presence or absence of an audio signal in the received signal from the received signal, and outputs a signal sp [voice detection flag] indicating the presence or absence of the audio signal in the transmitted signal from the noise canceller NC (5). ] Is received. Based on the result, the double talk determination unit DTD (7) determines which of the transmission and reception signals contains the audio signal.

In response to the result of this judgment, the LOSS determining section (8) sets L to be inserted into the transmission system / reception system based on the setting.
The OSS is determined, and R_loss is notified to the amplifier (2) and S_loss is notified to the noise canceller NC (5).

As this setting, for example, a certain amount of VS
_Loss (for example, −12 dB) is inserted into one of the transmission and reception.

There are four cases depending on the presence or absence of voice, and are set as follows. (1) Receive (no voice) / Transmit (no voice): S_lo
ss = VS_loss (2) Reception (with voice) / Transmission (without voice): S_lo
ss = VS_loss (3) Receive (no voice) / Transmit (with voice): R_lo
ss = VS_loss (4) Received (with voice) / Transmitted (with voice): S_lo
ss = VS_loss The attenuation of the non-inserted VS_loss is “0”
And

This setting can be changed as appropriate. For example, when switching the voice switch (VS_lo
Since the amount of attenuation changes rapidly when switching from ss to "0", the user feels a so-called switch feeling.
In order to reduce this, it is possible to make the amount of attenuation slope at the time of switching.

The signal attenuation determined by the voice switch (A) and the signal attenuation determined by the noise canceller (B)
Thus, the signal attenuation of the transmission / reception signal is determined.

In this embodiment, the signal attenuation of the received signal is the signal attenuation of the voice switch (A), and the signal reduction of the transmission signal is the final value of the noise canceller controlled by the signal reduction (A) of the voice switch. This is the signal attenuation (C).

That is, if the signal attenuation calculated by the noise canceller for noise reduction is larger than the signal attenuation provided by the voice switch, the signal attenuation of the noise canceller is adopted, and the noise cancellation is made smaller than the signal attenuation provided by the voice switch. If the signal attenuation is small, the signal attenuation provided by the voice switch is adopted.

Therefore, the final signal reduction amount of the transmission signal changes with the signal attenuation amount provided by the voice switch as an upper limit.

The presence / absence of a voice signal on the transmitting side may be determined by taking in the voice signal with a voice switch and performing similar processing, but in the present embodiment, the presence / absence of voice in the voice signal is determined by the noise canceller. The setting uses judgment.

Next, the operation of the noise canceller will be described.

The noise canceller is, for example, a DSP (Digita
l Signal Processor), and the processing program is stored in a memory in the noise canceller or a memory attached to the control circuit. FIG. 2 is a block diagram of a noise canceller showing a functional configuration realized by the processing program.

A digital audio signal obtained by A / D converting an audio signal from an audio input unit such as a microphone is first input to a frame division unit 21. The frame division unit is, for example, 12
The frames arranged into eight samples are output (frame division step). At this time, the digital transmission signal may be divided into, for example, frames of 80 samples, and then the frame ends may be overlapped by windowing. The digital transmission signal frame is input to a fast Fourier transform unit (FFT) 22.

The output of the FFT 22 is subjected to noise suppression in the multiplier 23 based on the output from the final reduction amount determining section 34 for determining the final signal reduction amount (C) of the noise canceller.
IFFT unit 24 performs inverse FFT and frame synthesis unit 25
To return to the frame and output as a transmission signal.

The output of the FFT 22 is input to a band power calculator 26, and the output is supplied to a significant value calculator 27 and a band-specific gain determiner 33. Update determination unit 3
According to the determination result of 1, the output is also supplied to the noise leak integration value updating unit 32.

The output of the significant value calculator 27 is sent to the update determiner 31
And a voice weight calculator 28.

The output of the noise leak integrated value updating unit 32 is supplied to a significant value calculating unit 27, a voice weight calculating unit 28, and a band-specific gain determining unit 33.

The output of the voice weight calculator 28 is supplied to the noise minimum value estimator 29 and the band-specific gain determiner 33, and the SP value (voice detection flag) is supplied to the voice switch VS.
Is output as

The band-specific gain determining section 33 receives the outputs from the noise leak integrated value updating section 32, the noise minimum value estimating section 29, and the speech weight calculating section 28 as input, and determines the final reduction amount determining section 34.
Output a signal to

The final reduction amount determination unit 34 receives S_loss from the voice switch VS and the output from the band-specific gain determination unit 33 as inputs, and outputs a gain to the multiplier 23.

The operation of each block will be described below.

The fast Fourier transform unit FFT22 performs a fast Fourier transform process on the input digital transmission signal frame, and sequentially performs 16 bands (k =
0, 1, 2,... 15) are obtained. This transform coefficient need not be the same in each band. The band-divided transform coefficients are output to the band power calculator 26 (frequency band dividing step). <Band Power Calculation> The band power calculation unit 26 obtains the energy (mean square value of the conversion coefficient) for each band, takes the logarithm, and calculates the band power channel_power (m, k), [m is the frame number, and k is the band. No. (0 to 15)] (power calculation step for each band). This band power is output to the significant value calculation unit 27. <Significant value calculation> In the significant value calculating unit 27, the noise leak integrated value output from the noise leak integrated value updating unit 32 described later
noise_power (m, k) and the above band power channel_power
The difference tmp from (m, k) is obtained, and the difference tmp for each band is compared with a predetermined threshold value. Differences by band above arranged in frequency order
When it is determined that the difference tmp by band of a plurality of adjacent bands among the tmps exceeds the threshold value, the difference tmp by band is given a predetermined weight and added to each other. The conditional sum of the weighted values suby (m, k) (when it is determined that the difference tmp by band of a plurality of adjacent bands exceeds the threshold) is output as a significant value y (significant value calculating step). ).

The average value of the significant value y (y_average: an estimated value obtained by leak integration, for example, calculated by the following equation) is also output.

Y (m): Significant value, conditional sum of suby (m, k) y_average (m) = y_average (m-1) × 0.9 + y (m) × 0.1 FIG. It is a flowchart which shows a procedure. A flow for outputting the significant value y will be described with reference to FIG.

After resetting / initializing the frame number m to 0 in step 3a, the group number m is incremented and the significant value y and the band number k are incremented in step 3b.
And the continuous number flag (continuous number flag of the difference tmp for each band exceeding the threshold value) is initialized to “0”.

Next, in step 3c, for band k = 0,
The difference tmp between the band power and the noise leak integral value and the value suby (m, k) obtained by weighting the difference tmp for each band are calculated as follows.

Tmp = chanel_power (m, k) −noise_power (m, k) sub_y (m, k) = {200− (k−1) ² } / 100 × (tmp−1) where {200− (k−1) -1) ² ｝ is a weighting coefficient. In this case, the band is set to decrease as the frequency of the band increases, but can be changed as appropriate.

When the difference tmp for each band at the band k = 0 is calculated, the significant value calculation unit 27 determines in step 3d the difference tm for each band.
Compare p to a threshold value (eg, 1). If the threshold is exceeded, it is determined that there is a possibility that the sound is voice, and step 3 is performed.
e, the process proceeds to step 3i via step 3g,
Set flag to 1. Then, in step 3k, the band number k
Is incremented to set k = 1, and the process returns to step c to execute the same processing for the band k = 1.

Here, it is assumed that the band-by-band difference tmp exceeds the threshold value after the band k = 0 even in the band k = 1. Since the continuation number flag is already 1, step 3e to step 3f
Then, the operation of y = y + suby (m, k−1) is executed. Then, set the continuous number flag to 2,
After step 3g, the process proceeds to step 3h to execute the following calculation.

Y = y + suby (m, k) Then, in step 3k, the band number k is further incremented to set k = 2, and the process returns to step 3c to execute the processing for band k = 2.

Thereafter, similarly, the difference tmp by band between adjacent bands
Each time exceeds the threshold, the suby (m,
k) is sequentially added to the significant value y obtained up to the immediately preceding band, and a weighted added value y of the band-based difference tmp is obtained.

When the difference tmp for each band becomes equal to or less than the threshold value in any band k = i, the significant value calculation unit 27
Moves from step 3d to step 3j,
Is reset to 0.

When the processing is completed for all 16 bands (k = 0 to 15) constituting one frame,
The significant value calculation unit 27 proceeds from step 3m to step 3n, and outputs the significant value y and the weighted difference suby (m, k) (k = 0 to 15) calculated for each band after weighting.

In this way, a significant value y is obtained for each frame, and is used to determine whether the frame is a speech frame or a noise frame.

The significant value calculation section 27 also counts a significant section for determining the noise power forced update. This processing will be described with reference to the flowchart of FIG.

First, an average value y_average (m) of the significant values y (m) is obtained.

In step 4a, frame number m = 0, sum
_Average (0) = 0.1, y_average (0) = 10, counter (0) = 0
, The group number m is incremented and a significant value y, sub (m, k) is input in step 4b.

Then, in step 4c, the average value of the significant value y is calculated. The average value can be set to an appropriate period based on the relationship between the memory capacity and the calculation amount (for example, 0.1 to
It is enough to take an average of about 0.3 seconds.
For example, an average is obtained by adding 0 frames), and in general, estimation is calculated as follows using leak integration. Needless to say, a method other than leak integration may be used for obtaining the average value.

Y_average (m) = y_average (m−1) × 0.9 + y (m) × 0.1 Next, in step 4d, the sum of absolute values sum of the difference between sub (m, k) and sub (m-1, k) Is calculated (step of calculating the sum of significant values for each band), and in step 4e, the ratio r is calculated by dividing the sum by the average value sum_average of the absolute sum sum (significant value normalization step).

Sum (m) / sum_average (m−1) This value may be directly used as r, but in order to remove a specific value, the attenuation rate determined by r (m−1) (for example, 0.99 )
Is compared with the value obtained by multiplying the value, the larger value is adopted as r (m).

The ratio r serves as a criterion for the counter addition for calculating the significant value section. For example, the upper limit is set to 8. Therefore, if it is determined in step 4f that r (m) exceeds 8, r (m) = 8 is reset in step 4g.

Next, sum_average is updated in step 4h. The average value can also be set to an appropriate period based on the relationship between the memory capacity and the calculation amount (for example, 0.1 to
It is enough to take an average of about 0.3 seconds.
In general, it can be estimated and calculated as described below using leak integration. Needless to say, a method other than leak integration may be used for obtaining the average value.

Sum_average (m) = sum_average (m−1) ×
0.9 + sum (y) × 0.1 Note that sum_average may use an estimated value of the standard deviation.
Also in this case, an estimated value can be obtained by using the leak integral of the following equation, and this value is used instead.

Sum_average (m) = sqrt (sum_average (m−
1) ² × 0.9 + sum (m) ² × 0.1) Subsequently, the counter (m) of the significant section is calculated.

Y> 10 and counter (m) <100 and r (m)
When ≤ THR, 1 is added to counter (m). If this condition is not satisfied, counter (m) is reset to 0.

THR may be a fixed value, and y_avera
It can be changed by ge. In the present embodiment, the THR that changes according to the following equation is adopted.

THR = 1.7 + (y_average−40) / 200
However, 1.7 ≦ THR ≦ 2.0 y_average> 100 THR = 2.0 y_average ≦ 40 THR = 1.7 40 ≦ y_average ≦ 100 THR = 1.7 + (y_average−4
0) / 200 Therefore, when it is determined in step 4i that y_average (m) exceeds 100, THR is set to 2.0 in step 4j, and it is determined in step 4k that y_average (m) exceeds 40. In this case, in step 41, THR is set to a variable value in the above equation. In other cases, THR is set to 1.7 in step 4m.

At step 4n, it is determined that the significant value y exceeds 10, and at step 4o, the counter counter is set to 10
If it is determined that the ratio r is less than 0 and the ratio r is determined to be equal to or less than THR in Step 4p, the counter counter is
Is added, otherwise the counter counter is reset to 0 in step 4r.

Similarly, if it is determined in step 4n that the significant value y is 10 or less, in step 4s the counter counter (m) is determined.
Is reset to 0, and counter is 100 in step 4o.
In the case of above (ie, 100), count 4
r (m) = counter (m−1).

With the above processing, coun
ter (m) and y_average (m) are output (step 4u). <Update judgment> These outputs (counter (m), suby (m, k), y
(m), y_average (m)), the update determination unit 31 determines whether or not the noise power value noise_power (m, k) for each band has been updated.
The noise leakage integrated value updating unit 32 updates the noise power value for each band.

Significant value y is 20 to 30 for normal speech
And if noise estimation is well performed, y <
It will be about 15. Therefore, when y <15, for example, the following equation is used (first noise power estimation value updating step). noise_power (m + 1, k) = noise_power (m, k) × 0.9 + chan
nel_power (m, k) × 0.1 k = 0,1,..., 15 IS127 [Variable-rate speech coding system of US standard: “Enhanced VariableRate Codec, Speech Service O
ption 3 for Wideband Spread Spectrum Digital Syste
ms "(TIA IS127)], a normal noise power update may be performed.

If y is not accurately calculated for some reason, forced updating is performed based on the counter value (counter) (second noise power estimation value updating step). For example, counter (m) ≧ 100 and y <y_average (m) +5
At the time of updating, it is updated according to the above equation.

Subsequently, the band-specific gain determining section 33 determines the gain for each band. At this time, the value is set for each band with reference to the significant value (y), the significant value (suby) for each band, and the like calculated by the significant value calculation unit. <Speech Weight Calculation> Upon receiving the significant value y output from the significant value calculation unit, the speech weight calculation unit calculates the speech weight sp used for determining the noise suppression gain. The voice weight sp is defined as a degree of voice included in one frame, 0 ≦ s.
is a numerical value expressed in the range of p ≦ 6, where sp = 0 is a noise section,
sp = 6 represents a voice section. It should be noted that the numerical value, the step division, and the like can be set as appropriate.

This sp value is supplied to the above-mentioned voice switch, and is used for the voice switch to determine the presence or absence of voice in the transmission signal. For example, when sp = 0, it is determined that there is no voice, and otherwise, it is determined that there is voice.

FIG. 5 is a flowchart showing the procedure for calculating the speech weight sp in the speech weight calculator 28 and the processing contents thereof.

First, after resetting the frame number m to 0 in step 5a, the group number m is incremented in step 5b. Next, in step 5c, the weighted addition value y is compared with an arbitrary threshold value “13”, and y <13
If so, it is determined that the frame is a noise frame, and the process proceeds to step 5d, where the speech weight sp (m) is set to sp (m) = sp (m-1) -0.5. As will be described later, sp (m) is set in the final step so that sp (m) = MAX (sp (m), 0)) and the minimum value becomes 0. Therefore, if noise frames are continuous, sp (m) Converges to zero.

On the other hand, if y.gtoreq.13, the frame is in a voice or transitional period, and the process proceeds to step 5e to calculate a temporary voice weight zz = (y-13) .times.1.5 + 1.

First, it is determined in step 5f that sp (m-1) ≦ 0.5. That is, the speech weight sp one frame before.
It is determined whether (m-1) is sufficiently smaller than 0.5 or less, and it is determined whether the frame is a noise frame.

When the previous frame is determined to be a noise frame, that is, when sp (m-1) is 0.5
In the following cases, the process proceeds to step 5g, where the voice weight sp (m) of the current frame is set to the temporary voice weight z.

This case is at the time of switching from the noise to the voice, and it is necessary to suppress the noise and raise the voice clearly so that the beginning of the word is not cut off. Therefore, the audio weight is set to take a large value.

On the other hand, the speech weight sp of the previous frame is
When (m-1) is not a noise frame (sp (m
In -1)> 0.5), the process proceeds to step 5h, where z> sp (m-1) +0.5 is determined. If z is greater than (sp (m-1) +0.5), in step 5i the speech weight sp (m) of the current frame
Is set to (sp (m-1) +0.5).

This case is a point in time when it is determined that the audio frame is in a transitional period. The importance is placed on continuity, and the rise of z from the previous frame is suppressed to 0.5.

On the other hand, if z is equal to or smaller than (sp (m-1) +0.5), the flow shifts to step 5j to judge that z <sp (m-1) -0.5, and z is equal to (sp (m) If it is smaller than -1) -0.5), the voice weight sp (m) of the current frame is set to (sp (m-1) -0.5) in step 5k.

This case is also a point in time when it is determined that the audio frame is in a transition period, and the continuity is emphasized, and the drop of z from the previous frame is suppressed to 0.5.

If z is equal to or smaller than (sp (m-1) -0.5), the flow shifts to step 5m to set the speech weight sp (m) = z of the current frame.

Through the above steps, sp (m) = z,
sp (m-1) ± 0.5 is set to one of three values, and finally sp (m) = MIN (sp (m), 6) sp (m) = MAX (sp (m) , 0) determines the value of sp (m) = 0 to 6.

That is, steps 5f to 5
m, the temporary voice weight z calculated in the current frame is
It is corrected in consideration of the voice weight sp (m-1) set in the immediately preceding frame, output as sp (m) in step 5n, returns to step 5b, and returns sp to all m.
(M) is required.

By using the voice weights sp (m) obtained in this way, it is possible to adjust the voice / noise / transient range in consideration of the continuity between frames.

The speech weight sp (m) obtained by the speech weight calculator 28 is input to the noise minimum value estimator 29 and the band-specific gain determiner 33.

The sp value is also supplied to the voice switch VS as a voice detection flag. Based on this, the VS determines, for example, that sp = 0 [no sound] / sp> 0 [voice]. <Estimation of Noise Minimum Value> The noise minimum value estimation unit 29 calculates the leak integrated value noise_power of noise in each band every 100 frames in which the speech weight sp becomes sp = 0.
Check the minimum value of (m, k). Then, this minimum value is calculated by the following 1
In the period of 00 frames, the noise minimum value noise_min
Used as (m, k). At the same time, an inter-band average value min_all of the noise minimum value of each band is obtained.

FIGS. 6 and 7 show the noise minimum value estimating unit 2.
9 is a flowchart showing the procedure and contents of a minimum value estimation process executed in FIG.

In the figure, the noise minimum value estimating unit 29 first resets the frame number m to m = 0 at step 6a, sets the frame counter value to fc = 96, and sets the noise minimum value to noise_min (k) = 36, the band is set to k = 0,.
.. Initially set to 15, respectively.

Further, noise_min_h (k) = MAX (noise_power (m, 2k), noise_p
ower (m, 2k + 1)), k = 0,..., 7 The noise-to-band average min_all of the noise minimum is noise_min_h (n):
Initially, min_all = Σnoise_min_h (n) / 8 n = 0 to 7, which is the average of the sum of the values of n = 0, 1,..., 7.

That is, a value having a large noise power in an adjacent band is taken, and the average value is set as min_all.

Next, the noise minimum value estimating section 29 determines in step 6
After incrementing the frame number m in b, it is determined in step 6c whether the speech weight is sp = 0, that is, whether the frame is a noise frame.

If the frame is a noise frame, the flow returns to step 6b to increment the frame number m, and the noise frame is determined in step 6c. sp =
If it is determined that the value is not 0, that is, if a voice frame or a transition frame is detected, the minimum noise value estimating unit 29 proceeds to step 6d, where the frame counter fc is incremented and the band k = 0. Select

After setting x = MAX (noise_power (m, 2k), noise_power (m, 2k + 1)) in step 6e, the process proceeds to step 6f to determine whether noise_min_h (k)> x. judge.

If noise_min_h (k)> x, step 6
g, where the minimum noise value is noise_min_h (k) = x
Set to. Then, control goes to a step 6h.

On the other hand, if noise_min_h (k) ≦ x, the process directly proceeds to step 6h to select the next band k = 1, and the above-mentioned steps 6e to 6e until the band k = 8 is reached.
The process of setting the noise minimum value noise_min_h (k) in step 6g is repeated.

When the band k reaches 8, the noise minimum value estimating unit 29 determines whether or not the frame counter fc has reached 100 in step 6j. Until the number of frames reaches 100, the process returns to step 6b to select the next frame, and the processes in steps 6c to 6i are repeated for the selected frame.

On the other hand, when the processing for the above 100 frames is completed, the minimum noise value estimating section 29 proceeds to step 7a, where the inter-band average (min_all) of the minimum noise value is calculated as noise.
e_min_h (n): Calculated as the average of the sum of the values of n = 0, 1,..., 7 as follows.

Min_all = Σ noise_min_h (n) / 8 n = 0-7 Further, noise_min (0) and noise_min (1) are respectively changed to noise_min (0) = noise_min_h (0) noise_min (1) = 0.75 × noise_min_h ( 0) + 0.25 × noise
_Min_h (1) and the band is k = 1.

Further, the minimum noise value estimating section 29 proceeds to step 7b, where the remaining bands k = 8 to 8 based on the eight noise minimum values previously determined for the bands k = 0 to 7. 1
Noise minimum value for 5 is noise_min (2k) = 0.75 × noise_min_h (k) + 0.25 × nois
e_min_h (k-1) noise_min (2k + 1) = 0.75 × noise_min_h (k) + 0.25 × no
It is calculated as ise_min_h (k + 1).

When the above operation is completed, the noise minimum value estimating unit 29 proceeds from step 7d to step 7e, where noise_min (14) = 0.75 × noise_min_h (7) + 0.25 × nois
e_min_h (6) noise_min (15) = noise_min_h (7) is calculated.

That is, the minimum noise value estimating unit 29 interpolates 16 min_all based on 8 min_all in the steps 7a to 7e.

When 16 min_all are calculated in this way,
In step 7f, the noise minimum value estimating unit 29 resets the frame counter fc to 0, sets the noise minimum value to noise_min_h (k) = 36, and sets the band to k = 0,.
・ Set to 7 again.

Then, in step 7g, the inter-band average value min_all of the noise minimum value calculated previously and the noise minimum value noise_min (m, k), k = 0,...
Returning to step 6b, similar calculation processing of the minimum noise value and the average value between bands is repeated for the next frame (m = m + 1). <Band-Specific Gain Determination> The band-specific gain determination unit 33 determines the band power channe output from the band power
l_power (m, k), noise power noise_power (m, k) output from the noise leak integration value update unit 32, voice weight sp (m, k) output from the voice weight calculation unit 28, and noise minimum value estimation Noise minimum value noise_min (m, k) output from the unit 29
, The gain for each band gain (m, k) is determined.

First, the noise leak integrated value noise_power (m, k)
Noise_power (m, k): k =
Noise_all = Σnoise_power (m, k) / 16 k = 0 to 15 as an average of the sum of the values of 0, 1,..., 15.

Subsequently, the band power channel_power (m, k)
Band minimum value min_band and noise minimum value noise_min (m,
The band maximum value max_band of k) is defined as min_band = MIN (channel_power (m, k), k = 2,.
.., 11) max_band = MAX (noise_power (m, k), k = 0,...)
・, 15)

Next, the adjustment value md common to the bands is given by md = (noise_all−min_all) × (1−sp / 6) + (min
_Band−max_band) × sp / 6. According to this equation, when sp = 0, that is, in a noise section, md = noise_all−min_al
l sp = 6, ie, in the voice section, md = min_band−max_ban
d, indicating that the transition region takes an intermediate value between these values.

FIGS. 8 and 9 show examples of frequency versus power characteristics for a noise frame and a speech frame, respectively.

In a noise frame, as shown in FIG. 8, the band power is close to the noise minimum. The value obtained by adding the adjustment value to the noise minimum value is obtained by changing the average value to the noise noise average value noise_all while keeping the spectral characteristics of the noise minimum value.

On the other hand, in the case of a voice frame, FIG.
As shown in (2), the value obtained by adding the adjustment value to the noise minimum value is adjusted so that the maximum value of the band coincides with the minimum value of the band power while maintaining the spectral characteristics of the minimum value.

The gain for each band gain (m, k) is the band power cha
nnel_power (m, k), noise minimum value noise_min (m, k),
It is determined as follows from the adjustment value.

First, tmp = channel_power (m, k) −noise_min (m, k) −md−1.62
Set to 5.

Next, gain (m, k) (g
ain (m, K) ≦ 0) Change the method of decision. (1) When sp> 0, that is, when voice or a transient frame, gain (m, k) = ｛sqrt (1.4+ (0.7 × tmp) ² ) + 0.7 × tmp
−10｝ × 2 (2) When sp = 0, that is, for a noise frame, gain (m, k) = [sqrt (1.4+ (0.03125 × tmp) ² ) +0.03125
× tmp−10] × 2 This is obtained independently for k =,.

The function form for determining the gain can be set as appropriate. It is sufficient that the voice frame is lower than the noise frame in an area where the value of tmp is small.

The gain for each band gain (m, k) obtained as described above is multiplied by a transform coefficient for each band in the multiplier 23, thereby performing noise cancellation.

FIG. 10 is a graph showing the relationship between tmp and gain. The audio frame (sp>) is indicated by a solid line.
0), and the dotted line is the case of a noise frame (sp = 0).

When tmp is less than 0, the gain of the voice frame is lower than the gain of the noise frame. It can be considered that tmp is obtained by subtracting md and a constant (1.625 in the above example) from the SNR of the band, so that although there is a variation in the adjustment value md, the SN of the band is
When R is small, the voice section takes a smaller gain value than the noise section.

This is because a band showing a small SNR in a voice section (this is a band which can be estimated to contain no voice component) is positively suppressed (small gain value) to include a voice component in a voice frame. The result is to make the band stand out. This effect can be achieved by setting the gain smaller than the band gain value of the noise frame.

Such a gain value setting is not limited to the above-described hyperbolic function, and can be performed by various settings.

For example, as shown in FIG. 11, in the case of a voice frame and a transient frame, gain (m, k) = − 20 tmp <0 tmp × 2−200 0 ≦ tmp ≦ 100 tmp> 10 In the case of a noise frame, gain (m, k) =-18 can also be set.

The noise-cancelled transform coefficient for each band is subjected to inverse fast Fourier transform in IFFT 24 and returned to a signal frame on the time axis, and is then frame-synthesized in frame synthesizing unit 25 as a transmission signal. For example, it is supplied to a speech encoding circuit.

As described above, according to this embodiment,
Even in a frame determined to be a voice frame, a gain smaller than a band-specific gain of a frame determined to be a noise frame is set for a band determined not to include a voice component. Band) is emphasized, and as a result, an acoustically good noise suppression output signal can be obtained.

Further, the minimum value of the noise power in each band is obtained in the noise minimum value estimating circuit 29, and the spectrum shape of the noise minimum value is used for the determination of the gain for each band by the gain determining unit 33 for each band. For example, it is possible to realize a noise canceling process that is not affected by a short-term change in a noise spectrum such as when a car passes, and does not easily distort the voice spectrum.

[0156] Also, a frame in which the significant value y of each frame is large (usually judged to be speech) but the change in the difference of the band-wise difference from the previous frame is small (however, judgment is made by normalizing with the average value). When continuous (for example, 100 frames)
Judge as a noise frame, and forcibly update the noise power estimation value. At the time of this forced update determination, the continuous section is counted using the value normalized by the average value of the spectrum deviation, so even if the noise is such that the spectrum deviation varies between frames, it is counted as a substantially continuous section. can do. Therefore, even if there is a change in a significant value such that a good noise frame determination is not made, a good update of the noise power estimation value becomes possible by performing the forced update, and thus good noise suppression is performed.

After the signal reduction amount (B) of the noise canceller is determined as described above, the final reduction amount determining unit 34 for adjusting the final signal attenuation amount (C) determines the S_loss and gain supplied from the voice switch. Based on this, the final signal attenuation (lg) of the transmission signal is determined.

This signal attenuation is determined, for example, as follows.

Lg (m, k) = MIN (S_loss
(M), gain (m, k)) The smaller of S_loss and gain (m, k), that is, the larger of the signal attenuation is adopted.

FIG. 12 shows samples of the transmission signal and the reception signal, and FIG. 13 shows samples of the power transitions of S_loss and lg.

Since lg is always equal to or less than S_loss,
The communication system (send-receive) must be VS_loss or less.
OSS is inserted. S_lo for only transmission
Since ss = 0, the original noise suppression of the noise canceller is realized. At the time when the transmission voice ends, in the above example, since gain <S_loss, the feeling of switching by the voice switch (phenomenon in which the sound is unnaturally reduced due to abrupt switching of the LOSS of the transmission / reception system) is reduced.

Next, the operation of the voice switch will be described.

The above-described noise canceller may also be provided on the receiving side to determine the presence or absence of voice. In this embodiment, the presence or absence of voice in the received signal is set to be performed by the double talk determination unit DTD. Various methods can be adopted as the determination method, and an example will be described with reference to FIG.

In this example, the presence / absence of voice is determined by comparing the frame power P (for example, P = 10 log (mean square value of the sample)) of each frame of the received signal with a predetermined reference.
At the time of this determination, the long-term average avg of the minimum values min and P of the frame power P during the noise level update period INTVL (for example, 1 second: equivalent to 50 frames) (for example, the leak integration value:
avg = γavg + (1−γ), and γ is appropriately set (for example, 0.99).

At step (2a), counter = 0 is set and the calculation is started. The initial value can be set as appropriate, for example, min = MAX_NOISE, noise = 5,
avg = 5 is set. MAX_NOISE is the maximum value of noise, and is set to, for example, 36.

In step (2b), the frame power P of the target frame is calculated / input.

In step (2c), the counter is incremented by "1", and in step (2d), the frame power P and min are compared. If P <min, min = P
(Step 2e), otherwise the current value of min is maintained and the process proceeds to the next step (2f).

In step (2f), a long-term average avg of the frame power P is obtained. For example, a leak integral value can be adopted as a long-term average value as in the following equation.

Avg = γavg + (1−γ), γ is appropriately set (for example, 0.99) In step (2g), the counter value is compared with the INTVL value. If they do not match, the process proceeds to step (2m) to output a noise value for the frame to be measured. If counter = INTVL, the process proceeds to the next step (2h) to update the noise value.

In step (2h), min-noise
> -2. If Yes, proceed to step (2i) and set noise = min. If No, the process proceeds to the next step (2j) to determine avg <noise-1. If Yes, go to step (2k), no
Set is = avg.

Then, the process proceeds to a step (2l), wherein
reset to ter = 0 and min = MAX_NOISE
To the next step (2m), and the updated no
Output an issue value.

The frame power P and noi for each frame
Using the se value as input, the presence or absence of a voice in the received signal is determined.

In the step (2o), the frame powers P and n
Input oise, and in the next step (2p), P <nois
e + TH is determined. TH is a threshold, for example, 18
Is set to If P <noise + TH, it is determined that the reception is absent [no voice signal] (step (2q)), otherwise it is received = available [voice signal is present] (step (2r)).

The result is output as the presence / absence of voice of the target frame (step (2s)).

By repeating this for each frame, it is possible to detect the presence or absence of voice in the received signal.

[0176] In response to this result, if there is a voice, a LOSS is inserted into the receiving side, so that the signal reduction rate of R_loss is executed by the amplifier. On the other hand, S_loss (signal attenuation (A)) is sent to the transmission side for comparison and adjustment with the signal attenuation (B) of the noise canceller.

The loss of the above voice switch is “0”
Although / VS_loss is a binary value, this setting can be changed as appropriate. For example, it can be set as follows. (1) Receive (no voice) / Transmit (no voice): R_loss = VS_loss-h; S_loss = h (2) Receive (voice) / Transmit (no voice): R_loss = 0; S_loss = VS_loss (3) ) Receiving (no voice) / transmitting (with voice): R_loss = VS_loss; S_loss = 0 (4) Receiving (voice) / transmitting (with voice): R_loss = 0; S_loss = VS_loss, where h = (sp) = Number of frames in which 0 continues) x (-
0.1) VS_loss ≦ h ≦ 0 sp: voice / noise determination variable received from the noise canceller An echo canceller EC (10) may be added to the above embodiment (FIG. 15). The echo canceller removes / reduces the signal when the output from the audio output unit is input from the audio input unit, and various types of echo detection methods can be adopted.

FIG. 2 except for the echo canceller EC (10)
And the explanation is omitted. In EC, the input signal from the audio input unit, the received signal input to the audio output unit, and the signal obtained by subtracting the received signal from the signal of the audio input unit are compared, and the received signal is not superimposed on the input signal It is determined whether the signal is superimposed, and if the signal is superimposed, the signal is subtracted and used as an input signal to the noise canceller NC.

Since the echo path changes according to the output voice environment, it is necessary to consider the time difference when the voice output from the voice output unit is received by the voice input unit.

In the above embodiment, a noise canceller is inserted on the transmitting side, but a noise canceller may be inserted on the receiving side. If a noise canceller is used for both transmission and reception, noise cancellation can be performed for both transmission and reception. In this case, the voice switch function is incorporated into the noise canceller, and the LOSS of the voice switch is controlled by controlling the noise signal attenuation of the noise canceller. It is also possible to double as an insertion function.

That is, it is sufficient to control the signal attenuation of both the transmission and reception so that the LOSS required for the voice switch function is always included.

The present invention is not limited to a communication device such as a mobile phone, but can be used for any device that uses voice processing (such as a recording device or a portable electronic terminal).

Note that each block shown in FIG. 2 is separately described for convenience of explanation, and each block does not have to be an individual element, and one or more functions, for example, a CPU , A DSP, a modem, a voice encoding circuit, and the like may be combined into a one-chip LSI.

[0184]

As described above, according to the present invention, it is possible to provide an electronic device capable of supplying a high-quality sound signal by using a combination of a noise canceller and a voice switch, thereby contributing to the industry. But it is a big thing.

[Brief description of the drawings]

FIG. 1 is a circuit block diagram showing an embodiment of the present invention.

FIG. 2 is a block diagram showing a noise canceller according to the embodiment of the present invention.

FIG. 3 is a flowchart showing a processing procedure of a significant value calculating unit according to the embodiment of the present invention.

FIG. 4 is a flowchart showing a procedure of counting a significant section for determining a noise power forced update according to the embodiment of the present invention.

FIG. 5 is a flowchart showing a processing procedure of a voice weight sp of the mobile phone according to the embodiment of the present invention.

FIG. 6 is a flowchart showing a processing procedure of a noise minimum value estimating unit according to the embodiment of the present invention.

FIG. 7 is a flowchart illustrating a processing procedure of a noise minimum value estimating unit according to the embodiment of the present invention.

FIG. 8 is a diagram illustrating an example of frequency versus power characteristics in the case of a noise frame.

FIG. 9 is a diagram illustrating an example of frequency versus power characteristics in the case of a voice frame.

FIG. 10 shows tmp-ga according to the embodiment of the present invention.
FIG.

FIG. 11 shows tmp-ga according to the embodiment of the present invention.
FIG.

FIG. 12 is a diagram showing samples of a transmission signal and a reception signal.

FIG. 13 is a diagram showing samples of power transitions of S_loss and lg.

FIG. 14 is a flowchart showing a processing procedure of the voice switch according to the embodiment of the present invention.

FIG. 15 is a block diagram of an embodiment of the present invention.

[Explanation of symbols]

NC: Noise canceller; VS: Voice switch

Claims (4)

[Claims] 1. A voice switch for inserting a signal reduction (A) LOSS into a transmission signal or a reception signal; and detecting a voice from the transmission signal or the reception signal to calculate a signal reduction (B) for noise suppression. And a noise canceller that performs LOSS insertion and noise suppression with a final signal reduction amount (C) adjusted by comparing the signal reduction amount (A) and the signal reduction amount (B). machine. 2. A final signal reduction amount (C) of a noise canceller.
2. The electronic device according to claim 1, wherein the electronic device is adjusted so as to be equal to or less than a signal reduction amount (A) of the voice switch. 3. The electronic apparatus according to claim 1, wherein said voice switch receives a result of voice detection by said noise canceller and inserts a LOSS into a transmission signal or a reception signal. 4. A noise canceller that performs voice detection from a transmission signal or a reception signal to suppress noise and a voice switch that receives a result of voice detection by the noise canceller and inserts a LOSS into the transmission signal or the reception signal. Electronic equipment characterized.