KR100294921B1 - The method and apparatus of speech detection for speech recognition of cellular communication system - Google Patents

Abstract

The present invention relates to a voice detection method and apparatus using only voice feature parameters generated by a vocoder. The voice detection method includes (a) extracting the voice feature parameter from a vocoder, and (b) using a voice feature parameter. A process of generating a signal, (c) generating a gain of a similar signal for each frame obtained by summing the absolute values of the similar signals, (d) obtaining a superimposed average of the similar signal gains over time, and (e) the similar signal The process of determining whether the current frame is a voice or a silent section between voice and voice using the superimposed average result of the gain and the results of previous frames, and notifying the starting and ending position information including the silent section between voice and voice. ; And (f) performing the process (e) again within a predetermined frame before and after the start and end positions of the voice section by using the result of step (e) to correct the voice output result. It is done.

According to the present invention, since voice detection is possible with a small amount of calculation, the voice detection function can be applied to an existing mobile phone using only software without adding hardware. Voice detection is possible even in a variety of noisy environments such as highways, enabling voice dialing while driving a car.

Description

The method and apparatus of speech detection for speech recognition of cellular communication system

The present invention relates to voice recognition of a mobile phone, and more particularly, to a method for selecting only a voice part from an input voice including noise in a mobile phone terminal.

Although there are many methods for detecting voice by receiving a voice signal, detecting a voice in a mobile phone is a different problem. First of all, the input is not the voice but the result of the encoder adopted by each mobile phone.

For example, in the CDMA method, the tenth order LSP (Line Spectrum Pair) value, the gain value and the pitch information for each frame are used. And the required calculation amount should be within 1 ~ 2 MIPS and the memory should be within 100KByte. Therefore, the conventional method of driving the decoder and reproducing the voice signal to detect the voice section is impossible in the CDMA or GSM mobile telephone. On the other hand, a method of detecting a voice using a gain value among voice feature parameters generated in a mobile phone is useful in a quiet environment, but the success rate is extremely low in a noisy highway environment.

1 and 2 show a conventional voice detection device.

First, FIG. 1 is a block diagram illustrating a voice detection apparatus using a gain parameter for each frame.

The input interface 110 extracts a voice feature parameter from the vocoder within a predetermined time from the packet data for each frame. The frame state determiner 120 determines whether the current frame is a voice, a silence section between the voice and the voice, or a background noise section using the gain parameter of the voice feature parameter to determine the first voice section. The first voice segment determination informs the start position and the end position information including the silence section between the speech and the speech. After the first voice section results, the post-processing unit 130 corrects the start position and the end position in more detail.

2 is a block diagram showing a voice detection apparatus using a reproduction signal.

The input interface 210 extracts a voice feature parameter from the vocoder within a predetermined time from the packet data for each frame. The input signal reproducing unit 220 generates a reproducing signal using the voice feature parameter. The gain generator 230 generates a gain of the reproduction signal for each frame obtained by adding up the absolute values of the reproduction signals. The frame state determiner 240 determines whether the current frame is a voice, a silent section between the voice and the voice, or a background noise section, using the result of the reproduction signal gain to determine the primary voice section. The first voice segment determination informs the start position and the end position information including the silence section between the speech and the speech. After the first voice section results, the post processor 230 corrects the start position and the end position in more detail.

The difficulty of voice detection in voice dialing of mobile phones is that the resources available are extremely limited, and that it is difficult to distinguish between noise and voice signals generated in real-world situations such as highways. More specifically, noise in real situations can be large in absolute noise signals. For example, the signal-to-noise ratio (SNR) on highways and national highways is between 6dB and -6dB. And there are various kinds of noise to be processed. You'll need to distinguish between the sound of your car's engine, the sound of the wind through a crevice, the sound of flickering or air conditioning, the sound of passing by your side of the car, and the thumping of the road. In addition, the characteristics of the input noise are time-varying. The absolute loudness of the engine sound or wind noise changes from time to time as the speed or direction of the car changes.

Therefore, in the case of FIG. 1, the voice detection capability is significantly reduced to 21% in the region where the signal-to-noise ratio is about 6dB to -6dB. In the case of FIG. 2, since the amount of calculation of the voice detection calculation is about 15 MIPS, there is a disadvantage that additional hardware must be added.

The technical problem to be achieved by the present invention is the voice detection method using a similar signal generation method that can apply the voice detection function to the existing mobile phone only by software without the addition of hardware because the voice detection ability is excellent and the voice detection is possible with a small amount of calculation In providing the device.

1 is a block diagram illustrating an apparatus for detecting a voice using a gain parameter for each frame.

2 is a block diagram showing a voice detection apparatus using a reproduction signal.

3 is a block diagram of an apparatus for detecting speech using the method for generating a similar signal according to the present invention.

According to an aspect of the present invention, there is provided a voice detection method using only a voice feature parameter generated by a voice vocoder, comprising: (a) extracting the voice feature parameter from the vocoder; (b) generating a similar signal using the voice feature parameter; (c) generating gains of the similar signals for each frame obtained by adding the absolute values of the similar signals; (d) obtaining a superposition average of the pseudo signal gains over time; (e) Determine whether the current frame is a voice or a silent section between voice and voice by using the superimposed average result of the similar signal gain and the results of previous frames, and the start position and the end including the silent period between voice and voice. Informing location information; And (f) performing the process (e) again within a predetermined frame before and after the start and end positions of the voice section by using the result of step (e) to correct the voice output result. It is done.

According to another aspect of the present invention, there is provided a speech detection apparatus for detecting speech using only speech feature parameters generated by a speech vocoder. An input interface for extracting parameters; A similar signal generator for generating a similar signal using the voice feature parameter; A pseudo signal gain generator for generating a gain of a similar signal for each frame obtained by summing the absolute values of the similar signals; A gain average calculating unit for obtaining a superposition average of the pseudo signal gains over time; A frame for determining whether the current frame is a voice or a silent section between the voice and the voice by using the result of the gain average unit and the results of previous frames, and notifying the start and end position information including the silent section between the voice and the voice. State determination unit; And a post-processing unit for correcting the voice output result by performing the frame state determining unit again within a predetermined frame before and after the result of the start and end positions of the voice section by using the result of the frame state determining unit.

Hereinafter, the present invention will be described in detail with reference to the accompanying drawings.

3 is related to a voice detection apparatus using a method for generating a similar signal according to the present invention, and includes an input interface 310, a similar signal generator 320, a similar signal gain generator 330, and a gain average calculator 340. And a frame state determination unit 350 and a post-processing unit 360.

The input interface 310 extracts voice feature parameters from the vocoder within a predetermined time from the packet data for each frame, unpacks the packet data of the vocoder, interprets the data, and inputs the data to the voice detection stage. do.

The similar signal generator 320 generates a similar signal using a voice feature parameter.

The similar signal gain generation unit 330 generates the gain of the similar signal for each frame obtained by taking the absolute value of the generated similar signal and summing it by the size of the frame.

The similar signal gain average unit 340 calculates an average value of four consecutive frames.

The frame state determination unit 350 determines whether the current frame is a voice, a silent section between the voice and the voice, or a background noise section, using the gain average value of the similar signal and the past state determination result. The first speech segment determination informs the start position and the end position information including the silence section between the speech and the speech.

The post-processing unit 360 corrects the start position and the end position in more detail by using the first speech section result.

The operation of the present invention will be described based on the above configuration.

The present invention uses only voice feature parameters generated by vocoder such as QCELP, EVRC and RPE-LTP. Unpacking the packet data of the vocoder, interpreting the data, inputting the data to the voice detection terminal, and extracting feature parameters within 1 to 2 msec from the packet data for each frame.

To generate a similar signal using the feature parameter, gain filtering is performed using a vocoder gain value on a white noise pulse, and then pitch filtering is performed using pitch information. The signal generated in this way is not a speech signal that can be distinguished by a human ear, but contains loudness and frequency information, which is basic information for distinguishing speech. Equation 1 generates an analogous signal.

x (i) = w (i) * G + x (i-l) * B

Where i is a time variable corresponding to the number of samples, G is a gain value per frame, L is a pitch per frame, B is a pitch gain per frame, x (i) is a similar signal, and w (i) is a white signal. .

Using this method, the signal reproducing apparatus of each vocoder can be replaced for real-time implementation of the voice detector in the mobile phone.

In order to generate the gain of the similar signal from the similar signal generated by Equation 1, the absolute value of the similar signal is taken and summed by the size of the frame. Each signal must be squared and added to find the square root to get the correct gain, but for real-time implementation, you cannot use multiplication or square root. Equation 2 is an equation for generating the gain of the pseudo signal.

s (j) = abs_sum (x (j * I) to x (j * (I + 1)-1))

Here, j corresponds to the number of frames j = i / I. I is a frame size of 160 (20 msec) in general. abs_sum (x (k) to x (m)) means the sum of absolute values from the kth similar signal to the mth similar signal.

In order to calculate the average of the similar signal gains, an average value of four consecutive frames is calculated as shown in Equation 3 below. The reason for using four consecutive frames in the present invention is that the feature of speech is the length of the frame that is best maintained.

nG (j) = (s (j-3) + s (j-2) + s (j-1) + s (j)) / 4

The gain of the similar signal for each frame has a large variation in time, and thus the probability of an error occurring during voice detection using the result of Equation 2 increases. Equation 3 has a more stable variation in gain than Equation 2, so that it is easy to distinguish between the voice part and the noise part.

The frame state determination unit 350 determines whether the current frame is a voice, a silent section between a voice and a voice, or a background noise section using the gain average value of the similar signal and the past state determination result to determine the first voice section. . The first voice segment determination informs the start position and the end position information including the silence section between the speech and the speech.

In addition, the detailed description of the frame state determination unit 350 and the terms used are as follows.

1. Terminology

X [i]: Average of similar signal gain of current frame

TH1: Value of 3.75 times the average energy value of the silent section. If it is smaller than this, the frame is a silent section.

TH2: Value corresponding to 6.25 times the average energy value of the silent section. If it is larger than this, the frame is a definite voice interval

LEN_TH: A number used to determine the end of the voice input process. It determines whether the voice input ends by comparing whether the length of the current silent frame is larger or smaller than this value from the end of the last voice. Usually 0.5 seconds is used.

2. Step by step description

(1) If X [i] is less than TH1, the interval is silent.

(2) If X [i] is greater than TH2, the interval is a negative segment.

(3) if X [i] is greater than TH1 and less than TH2,

1) If the previous frame is a voice section, the section is a voice section.

2) If the previous frame is not a voice section, the section is a silent section.

(4) In the case where the silent section is judged in the previous step, if there was a speech section at the previous status judgment stage, and the length from the end of the last speech section to the current frame is greater than LEN_TH, the speech detection is completed.

(5) When voice detection is completed, find the start position and end position of voice from all voice inputs.

The post processor 350 corrects the start position and the end position in more detail by using the first speech section result. This performs the state determination unit again within 10 frames before and after the start position result and 10 frames before and after the end position result to correct the voice detection result.

The inputs of the post processor 350 are position information of voice sections determined by the frame state determiner 340 and similar gain average values corresponding to the sections.

Looking at the post-processing step by step as follows.

(1) If the voice section is continuous, the pulse section length is obtained by using the start and end position information of the continuous section (or voice pulse section).

(2) If the length of the pulse section is smaller than the specified value (eg 0.04 seconds), it is incorporated into the silence section because the pulse section sound is not the voice but the surrounding noise.

(3) In consideration of the result of the 2nd step, check if there is any part where the silence section is longer than LEN_TH (0.5 sec).

3-1) If the first pulse or the last pulse is incorporated as muted by step 2, the start and end of the entire voice are also changed accordingly to complete the voice interval post-processing process.

3-2) When three or more pulses are present, when the pulses other than the first or last pulse are incorporated as silence, and the voices immediately before and after the voice are larger than LEN_TH (0.5 sec), the whole voice interval is divided into two parts. Find the start and end positions of the voice section, respectively, and find the length of that section. The larger of the lengths of the two parts thus obtained is selected to complete the postprocessing of the voice segment.

The following shows a table comparing the prior art and the present invention.

Table 1 compares a conventional frame-specific gain value and a voice detection result using a similar signal gain value according to the present invention in a CDMA terminal.

Class SNR 22 dB or more 15-10 dB -6 to 6 dB Gain Per Frame 95% 72% 21% Similar signal gain 95% 96% 75%

Table 2 compares the results of voice detection using the playback signal and the analogous signal according to the present invention in the CDMA terminal.

Class SNR 22 dB or more 15-10 dB -6 to 6 dB Pseudo signal 99% 96% 75% Play signal 99% 97% 81%

Table 3 compares the calculation amount of speech detection using the playback signal and the analogous signal according to the present invention in the CDMA terminal.

Class SNR Multiplication Plus number Total computation Pseudo signal 16000 / second 40000 / second 1 MIPS Play signal 320000 / second 720000 / second 15 MIPS

According to the present invention, since voice detection is possible with a small amount of calculation, the voice detection function can be applied to an existing mobile phone using only software without adding hardware. Voice detection is possible even in a variety of noisy environments such as highways, enabling voice dialing while driving a car.

Claims (7)

In the voice detection method using only the voice feature parameters generated by the voice vocoder, (a) extracting the speech feature parameter from the vocoder; (b) generating a similar signal using the voice feature parameter; (c) generating gains of the similar signals for each frame obtained by adding the absolute values of the similar signals; (d) obtaining a superposition average of the pseudo signal gains over time; (e) Determine whether the current frame is a voice or a silent section between voice and voice using the superimposed average result of the similar signal gain and the results of previous frames, and the start position and end including the silent section between voice and voice. Informing location information; And (f) using the result of step (e) to correct the voice output result by performing step (e) again within a predetermined frame before and after the start and end positions of the voice section. Voice detection method. The method of claim 1, wherein in step (b), the pseudo signal x (i) is x (i) = w (i) * G + x (i-L) * B Where i is a time variable corresponding to the number of samples, G is the gain value per frame, L is the pitch per frame, B is the pitch gain per frame, x (i) is a similar signal, and w (i) is a white signal to be. ) Voice detection method, characterized in that generated by. The method of claim 2, wherein in step (c), the similar signal gain s (j) is s (j) = abs_sum (x (j * I) to x (j * (I + 1)-1)) Where j is the number of frames and j = i / I. I is the size of the frame. Abs_sum (x (k) to x (m)) is the absolute value from the kth pseudosignal to the mth pseudosignal It means sum.) Voice detection method, characterized in that generated by. 4. The method of claim 3, wherein in the step (d), the overlap average nG (j) of the pseudo signal gain is nG (j) = (s (j-3) + s (j-2) + s (j-1) + s (j)) / 4 Voice detection method, characterized in that calculated by. A voice detection apparatus for detecting voice using only voice feature parameters generated by a voice vocoder, An input interface for extracting a voice feature parameter from the vocoder within a predetermined time from frame-by-frame packet data; A similar signal generator for generating a similar signal using the voice feature parameter; A pseudo signal gain generator for generating a gain of a similar signal for each frame obtained by summing the absolute values of the similar signals; A gain average unit for obtaining a moving average of the pseudo signal gains over time; A frame for determining whether the current frame is a voice or a silent section between the voice and the voice by using the result of the gain average unit and the results of previous frames, and notifying the start and end position information including the silent section between the voice and the voice. State determination unit; And And a post-processing unit for correcting the voice output result by executing the frame state determining unit again within a predetermined frame before and after the result of the voice section using the result of the frame state determining unit. Device. The method of claim 1, wherein (e) (e1) comparing the average signal gain average value of the current frame with a first threshold value corresponding to a silent period and a second threshold value corresponding to a voice interval; (e2) If the average value of the similar signal gain of the current frame is smaller than the first threshold, the interval is the silent section, and if the average value of the similar signal gain of the current frame is larger than the second threshold, the interval is the voice interval and the average value of the similar signal gain of the current frame. Determining that the section is a speech section if the previous frame is a speech section if the first frame is larger than the first threshold and less than the second threshold, and the section is a silent section if the previous frame is not a speech section; (e3) If the determination is made in the silent section in the above step, the process of completing the voice detection if the voice section is present in the previous status determination stage and the length from the end of the last voice section to the current frame is larger than the predetermined voice input end threshold. ; And (e4) If the voice detection is completed, the voice detection method comprising the step of obtaining the start position and the end position of the voice from the entire voice input. The method of claim 1, wherein (f) (f1) obtaining a pulse interval length using the start and end position information of the continuous interval (or voice pulse interval) if the voice interval is continuous; (f2) if the length of the pulse section is smaller than a predetermined value, the step of incorporating the silence section as the surrounding noise rather than the sound of the pulse section sound; And (f3) In consideration of the result of step (f2), check whether the length of the silent section is larger than the predetermined voice input end threshold, and if the first pulse or the last pulse is muted by the step (f2), The start and end of the voice are also changed accordingly, and when there are three or more pulses, when the pulses other than the first or the last pulse are incorporated as silence, the entire voice immediately before and after the voice becomes larger than the predetermined voice input end threshold. And dividing the voice section into two parts to obtain a start position and an end position of the voice section, respectively, and selecting the larger of the lengths of the two parts obtained by obtaining the length of the section.