JP2006208820A - Speech processor - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To provide a speech processor capable of outputting an inputted speech while improving articulation on a listening side. <P>SOLUTION: The speech processor comprises a frequency analysis section 1202 which frequency-analyzes the inputted speech signal, an allelic phoneme detection section 1206 which detect respective phonemic parts based upon the analysis result of the frequency analysis section 1202, an amplification processing section 1208 which selectively amplifies the phonemic parts according to the detection result of the phoneme detection section 1206 and attribute information of a user, and an output signal selection section 1210 which puts together and outputs the inputted speech signal and selectively amplified parts. <P>COPYRIGHT: (C)2006,JPO&NCIPI

Description

  The present invention relates to a configuration of a speech processing apparatus capable of improving the clarity of input speech and outputting the speech.

  Although humans communicate with each other under various noise environments, many previous studies have reported that speech perception is disturbed by noise (see, for example, Non-Patent Document 1). It has also been reported that non-native languages are more susceptible to noise than native languages (see Non-Patent Document 2, for example).

  Therefore, for example, in a foreign language speech learning material, if you want to acquire the ability to talk even in a noisy environment, the differences between native speakers and non-native speakers are detailed regarding the effects of adding noise to speech. It is necessary to investigate and consider effective training methods.

In this regard, the S / N ratio is systematically manipulated with respect to confronting speech in / r /-/ l / (hereinafter abbreviated as RL) in American English that is difficult for Japanese speakers to distinguish and perceive. There is a report on the results of an experiment examining the difference in correct answer rate between English native speakers and Japanese native speakers (see Non-Patent Document 3, for example).
Kalikow, DN, Stevens, KN, and Elliott, LL, Development of a test of speech intelligibility in noise using sentence materials with controlled word predictability, J. Acoust.Soc. Am., 61, pp.1337-1351, 1977 Florentine, M., Speech perception in noise by fluent non-native listeners, Trans. Tech. Comm. Physiol. Acoust., H-85-16, 1985 Kazuo Ueda, Ryo Komaki, Atsuko Yamada, Effects of Noise on American English / r /, / 1 / Perception, Proceedings of the 65th Annual Meeting of the Japanese Psychological Association 120 2001

  By the way, both acoustic differences and clues at the time of listening are different depending on the phoneme conflict. Therefore, for example, / b / and / v / (hereinafter abbreviated as BV) and / s / and / θ / (hereinafter abbreviated as STH) are phonemes that are difficult for Japanese speakers to distinguish and perceive. The impact may be different from RL. Thus, a phoneme that is difficult for a speaker who has a native language to distinguish and perceive is referred to as a “phoneme with a phoneme conflict”.

  Therefore, when the foreign language listening learning under the noisy environment as described above is to be realized by a computer, the noise is simply deteriorated by simply adding noise to the model voice to be heard by the learner from the beginning. There is a possibility that a sufficient learning effect cannot be obtained.

  Furthermore, not only in the case of learning foreign languages, but more generally, assuming that Japanese and foreigners communicate by voice communication, it is easier to hear due to the effects of ambient noise. Considering this, it is also necessary to consider the transmission / reception sound quality control.

  However, in the past, there has been a problem that it is not always clear what measures should be taken against the deterioration of the ease of hearing of sound due to ambient noise. In particular, when the native language of the sender / receiver is different from each other, it has not been sufficiently studied what kind of speech processing is desired to be performed.

  The present invention has been made in order to solve the above-described problems, and an object of the present invention is to provide an audio that can be output with improved clarity on the side of listening to the input audio. It is to provide a processing device.

  In order to achieve such an object, the speech processing apparatus of the present invention is a speech processing apparatus, which stores storage means for storing enhancement information of phonemes to be enhanced according to user attributes, and input speech A frequency analysis means for frequency analysis of the signal, a phoneme detection means for detecting each phoneme part based on the analysis result of the frequency analysis means, and a phoneme part according to the detection result and enhancement information of the phoneme detection means Emphasizing processing means for selectively emphasizing, and output signal selecting means for synthesizing and outputting the input audio signal and the selectively emphasized portion.

  Preferably, the phoneme to be emphasized is a plosive phoneme.

  Preferably, the phoneme detection means is a phoneme corresponding to a plosive sound depending on the presence or absence of a vertical pulse in which a certain level of power exists within a predetermined time from a low frequency band to a high frequency band in the analysis result of the frequency analysis means. Is detected.

  Preferably, the speech processing apparatus further includes a phonological acoustic model storage unit that stores an acoustic model, and detects phonology by likelihood calculation based on the acoustic model for each phoneme.

  Embodiments of the present invention will be described below with reference to the drawings.

(System configuration of the present invention)
FIG. 1 is a conceptual diagram showing an example of a communication system 1000 using the speech processing apparatus of the present invention.

  In the following description, a case where a sender and a receiver communicate with each other by a voice signal between remote locations using the voice processing apparatus of the present invention will be described by taking voice communication between computers as an example. However, the present invention is not limited to such a case, and more generally, other communication systems such as mobile phones, broadcasting systems such as televisions, and input audio are heard. It can be applied to systems that need to improve side clarity. For example, in a foreign language learning device as described above, when giving a listening task to a learner, by intentionally adding a predetermined level of noise, when aiming to improve listening ability in a noisy environment, Depending on the degree of training of the learner, it is also applied to the case where the model voice that has been processed to improve clarity is heard at first, and the original raw model voice is gradually trained. Is possible.

  Referring to FIG. 1, system 1000 includes a computer 100 for user 2 to perform voice communication with a user of a remote computer 300 via a network 400 such as the Internet. In the following description, the computer 100 functions as an audio processing device.

  Referring to FIG. 1, this computer 100 stores information in a disk drive 108 and a flexible disk (hereinafter referred to as FD) 116 for reading information on a recording medium such as a CD-ROM (Compact Disc Read-Only Memory). A computer main body 102 having an FD drive 106 for reading and writing; a display 104 as a display device connected to the computer main body 102; a keyboard 110 and a mouse 112 as input devices also connected to the computer main body 102; A microphone 132 as an input device and a speaker 134 as an audio output device are included.

  Note that the microphone 132 and the speaker 134 may be a headphone and a microphone worn by the user 2 using a headset.

  Note that the computer 300 basically has the same configuration as the computer 100.

  FIG. 2 is a block diagram showing the hardware configuration of the computer 100. As shown in FIG.

  As shown in FIG. 2, in addition to the disk drive 108 and the FD drive 106, the computer main body 102 constituting the computer 100 includes a CPU (Central Processing Unit) 120 connected to the bus BS and a ROM (Read Only). Memory) including a memory 122 and a RAM (Random Access Memory), a direct access memory device such as a hard disk 124, a microphone 132 or a speaker 134, and an interface for communicating with the network 400 128. For example, a CD-ROM 118 is attached to the disk drive 108. An FD 116 is attached to the FD drive 106.

  The CD-ROM 118 may be another medium, such as a DVD-ROM (Digital Versatile Disc) or a memory card, as long as it can record information such as a program installed in the computer main body. In this case, the computer main body 102 is provided with a drive device that can read these media.

  The main part of the speech processing apparatus of the present invention is composed of computer hardware and software executed by the CPU 120. Generally, such software is stored and distributed in a storage medium such as a CD-ROM 118 or FD 116, read from the storage medium by the CD-ROM drive 108 or FD drive 106, and temporarily stored in the hard disk 124. Alternatively, when the device is connected to the network 310, it is temporarily copied from the server on the network to the hard disk 124. Then, the data is further read from the hard disk 124 to the RAM in the memory 122 and executed by the CPU 120. In the case of network connection, the program may be directly loaded into the RAM and executed without being stored in the hard disk 124.

  The computer hardware itself and its operating principle shown in FIGS. 1 and 2 are general. Therefore, the most essential part of the present invention is software stored in a storage medium such as the FD 116, the CD-ROM 118, and the hard disk 124.

  However, a part of functions described below as software processing, for example, frequency analysis may be configured to be executed by hardware.

  FIG. 3 is a functional block diagram showing the configuration of the computer 100 functioning as the speech processing apparatus according to the present invention.

  As shown in FIG. 3, in the CPU 120, as a functional block, a frequency analysis unit 1202 that performs frequency analysis as will be described later and a clarification processing unit 1204 that performs speech clarification processing as functional blocks. And are included.

  Also, in the hard disk 124 connected to the CPU 120 by the bus BS, a phonological acoustic model database 1242 in which a phonological acoustic model used for detecting the presence of a plosive and the like and a user attribute database 1244 are stored. Yes. The phonological acoustic model is not particularly limited. For example, a hidden Markov model can be used. The user attribute database 1244 stores in advance information on phonemes that need to be emphasized in association with the attributes of the user (listener of the output sound) of the apparatus. That is, a phoneme including a plosive such as / b / needs to be emphasized by both Japanese native speakers and American English native speakers, while / r /, / l /, / s /, / Information that the phonemes such as th / need to be emphasized only when they are Japanese native speakers or users is stored. Further, it is assumed that the user 2 (speech input person) registers such attributes of the user in the system 1000 before using the apparatus.

  In the following description, it is assumed that “phoneme enhancement” is performed by selectively amplifying the phoneme portion. However, “phoneme enhancement” can also be performed on the phoneme by selectively attenuating unnecessary portions other than the phoneme.

  Further, the interface 128 converts the image data output to a video RAM (not shown) under the control of the CPU 120 and sent via the bus BS into a corresponding image signal and outputs the image signal to the display 104. Based on the image signal interface 1282, the audio converter 134 for converting into a corresponding audio signal based on the digital audio data sent via the bus BS under the control of the CPU 120, and outputting to the speaker 134, and the microphone 132. And an analog / digital converter (hereinafter referred to as A / D converter) 1286 for converting the analog audio signal into a corresponding digital audio signal. Although not shown in FIG. 3, for example, it is assumed that a storage area functioning as the video RAM and a storage area functioning as an audio signal input / output buffer are allocated in the memory 122.

  FIG. 4 is a block diagram for explaining the operations of the frequency analysis unit 1202 and the clarification processing unit 1204 described in FIG. 3 in more detail.

  Referring to FIG. 4, when an audio signal is input from microphone 132, A / D converter 1286 digitally quantizes the audio signal input as an analog electric signal.

  Subsequently, the frequency analysis unit 1202 performs frequency analysis by performing conversion using an algorithm such as FFT (Fast Fourier Transform) or wavelet conversion, and calculates the intensity of each frequency component included in the audio signal in time series. Divide and analyze.

  Further, a phoneme detection unit 1206 in the clarification processing unit 1204 detects each phoneme in the analyzed frequency component. Therefore, the phoneme detection unit 1206 detects all phonemes in addition to phonemes corresponding to plosives.

  The processing of the phoneme detection unit 1206 will be described more specifically as follows.

  First, the phoneme detection unit 1206 matches the detected phoneme with the data in the user database 1244, and if the detected phoneme needs to be amplified from the user attribute, the phoneme detection unit 1206 sends the phoneme to the amplification processing unit 1208. A portion of the signal within a corresponding range (time) is amplified, and when amplification is not necessary, amplification is not performed and the signal is output from the clarification processing unit 1204. Although not particularly limited, the phoneme detection unit 1206 may pass through the signal portion or amplify the signal to the amplification processing unit 1208 if the configuration shown in FIG. Processing may be performed with a rate = 1.

  Note that a plosive sound such as / b / can be detected as follows, for example.

    i) The phoneme detection unit 1206 detects the closing sound (silence or silent sound) of the spider that exists prior to the rupture. When there is no closing sound, the following processes ii) to iii) are not performed.

    ii) On the other hand, if a closing sound exists, the phoneme detection unit 1206 calculates a spectral envelope for the speech following the closing sound.

    iii) The phoneme detection unit 1206 calculates whether there is a vertical pulse or a noise pulse in which a certain level of power exists from a low frequency band to a high frequency band. Moreover, since these components generally appear in a time of 40 ms or less, they are regarded as a plosive component only when they occur continuously for a time shorter than this.

  For detecting other phonemes, an acoustic model for each phoneme created using speech uttered by a person based on data stored in the phoneme acoustic model database 1242 is used. A method for detecting whether or not a phoneme including it is generated is conceivable.

  The amplification processing unit 1208 performs amplification and sends data to the signal selection unit 1210 that performs subsequent processing. The amount of amplification in the amplification processing unit 1208 is performed with a preset default value or with a gain corresponding to the sound pressure of voice input in the past.

  The signal selection unit 1210 selectively synthesizes the non-amplified data sent from the phoneme detection unit 1206 and the amplified data from the amplification processing unit 1208 and sends them to the audio converter 1284.

  The audio converter 1284 performs a digital / analog conversion device for audio reproduction and reproduces it from the speaker 134. However, when digital audio data is further transmitted via another communication device (such as a mobile phone, a television / radio broadcast), the data is transmitted to the receiver after predetermined encoding.

  FIG. 5 is a diagram illustrating an example of a voice waveform input from the microphone 132.

  In FIG. 5, the English word speech “LAB” spoken by an American whose native language is English is shown as a waveform.

  FIG. 6A is a diagram showing the result of frequency analysis of the waveform of FIG.

  That is, when the waveform shown in FIG. 5 is subjected to frequency analysis, a voiceprint pattern as shown in FIG. 6A is obtained. In FIG. 6A, the vertically thinned portion of about 500 ms is a plosive component called “buzz bar”. Thus, when the power is weak (in the figure, the intensity of the power is indicated by the darkness of black), “B” may not be perceived and “V” may be perceived.

  FIG. 6B is a diagram showing a voiceprint pattern of a voice in which a plosive sound component is detected and only the plosive sound component portion is amplified.

  In FIG. 6B, the intensity of amplification is moderately amplified in accordance with the preceding voice, and is amplified with an envelope in order to improve the connection with the preceding and following voices. That is, the gain is gradually increased as the plosive portion is approached, and the gain is gradually decreased after the maximum gain.

  In FIG. 6B, the “LA” portion is not amplified, and the volume is increased as a whole by amplifying with the envelope, so that it does not sound harshly loud. However, since the plosive component is greatly amplified, the listener can perceive “B” and can perceive “LAB” as a word.

  In the following, an experimental result indicating an advantage of selectively amplifying a waveform component having a phoneme conflict such as a plosive as described above (referred to as a “phoneme conflict portion”) will be described.

[Experimental result]
Due to phonological conflict, acoustic differences and clues at the time of listening generally differ among listeners of different native languages. Therefore, for example, / b / and / v / (hereinafter abbreviated as BV) and / s / and / θ / (hereinafter abbreviated as STH) are phonemes that are difficult to perceive for Japanese native speakers. It may be different.

  Therefore, in the following experiment, Japanese native speakers (hereinafter abbreviated as JA) and American English native speakers (hereinafter abbreviated as AE) are targeted. An experiment was conducted to measure clarity by adding different noises. In addition, as a result of a preliminary experiment conducted with an American native English speaker, it was confirmed that the phoneme was affected by the sound pressure presented, so this was also verified.

(1 Experimental method)
(1.1 Stimulation)
A hand experiment was performed using English word pairs of the smallest phoneme pairs that oppose each other in three phonemes: RL pairs (right-1ight etc.), BV pairs (base-base etc.), and STH pairs (mouse-mouth etc.). For each confrontation, a total of 220 words of 50, 30, and 30 pairs (a total of 110 pairs) spoken by two American English native speakers (one male and one female) were used as stimulating speech. The voice recorded in the anechoic room was saved as a file in PCM (Pulse Code Modulation) format with an accuracy of 44.1 kHz and 16 bits for each word.

  As a stimulus for adding noise, the average of the sound pressure level (A characteristic) peak value when each word is output through headphones is 59 dB in the RL and STH conflicts, and 65 dB in the BV conflict. The amplitude was adjusted as follows.

  Adjusting the amplitude so that the peak value of the sound pressure level (A characteristic) when white noise and pink noise generated by the noise generator are output through headphones is in accordance with the SN of each condition, added to the sound used in this experiment did. Noises with a duration longer by 200 ms before and after the voice were superimposed.

  FIG. 7 is a diagram showing the SN ratio used as an experimental condition.

  Further, as a stimulus for measuring the influence of the presented sound pressure on the clarity, the average of the sound pressure level (A characteristic) peak when each word is output through the headphones is from 39 dB to 69 dB in each phoneme confrontation. The amplitude was adjusted in 5 dB steps.

(1.2 Experiment participants)
In the JA experiment, 11 university students who were native speakers of Japanese and had no experience of staying abroad for more than 3 months participated in the experiment. In the AE experiment, three American English speakers from the age of 23 to 43 participated in the experiment. All confirmed that they had normal hearing.

(1.3 Procedure)
The actual saponification was performed in a soundproof room for 3 days. Two English words that form the smallest phoneme pair were visually presented on the computer screen, and at the same time, either word was presented in both ears via headphones. Participants in the experiment judged and selected which word was the word pair on the screen.

(Noise-added voice session)
It was divided into two days according to the type of added noise. Each section consisted of two sections for each sound, and the order of the speakers was constant. Each section is composed of blocks for each phoneme confrontation including all SN-speech sounds, and presented in the order of RL, BV, and STH confrontation. All voice stimuli were presented in a random order within each block, and no feedback was given regarding the correctness of the answers.

(Sound pressure fluctuation session)
A sound pressure fluctuation session was conducted after the noise-added speech session. Except for the different stimuli, the structure and method were the same as for the noisy speech session.

(2 results)
(JA experiment)
FIG. 8 is a diagram showing the result of a noise-added voice session in the JA experiment.

  In any phonological conflict, it was shown that the correct answer rate tends to decrease when the SN ratio decreases.

  A two-factor ANOVA was performed for each phoneme confrontation, with the noise type and the signal-to-noise ratio as factors within the subject, and the correct answer rate as a dependent variable. In the BV conflict, the -9 dB condition of the white noise condition was excluded from the analysis. As a result, the main effect of the S / N ratio factor is significant in any phoneme conflict ([F (6,60) = 24.950, p <0.01], [<0.01] in the RL, BV, and STH phoneme conflicts, respectively). F (7,70) = 18.641, P <0.01], [F (6,60) = 32.15, P <0.01]) is the main effect and interaction of noise type factors Both were not significant.

  Next, FIG. 9 is a diagram showing the results of the sound pressure fluctuation session in the JA experiment.

  A two-factor ANOVA was performed with phonological confrontation and presented sound pressure as factors within the subject, and the correct answer rate as the dependent variable. As a result, the main effect of the presenting sound pressure factor was significant [F (6,60) = 10.503, P <0.01]. Although the main effect and interaction of phonological confrontation factors were not significant, when the correct answer rates of the 39 dB condition and the 63 dB condition were compared, the BV confrontation showed a greater change in the correct answer rate than the other phonological confrontation.

(AE experiment)
FIG. 10 is a diagram illustrating a result of a noise-added speech session in each phoneme conflict in the AE experiment. In any phoneme conflict, it was shown that the correct answer rate tends to decrease as the SN ratio decreases.

  Next, FIG. 11 is a diagram showing a result of a sound pressure fluctuation session in the AE experiment. The RL and STH conflicts showed little change in the presented sound pressure range used in the experiment, but the BV conflict showed that the correct answer rate was susceptible to the presented sound pressure.

  Summarizing the above analysis results, the correct answer rate decreased with a decrease in the S / N ratio in all phoneme confrontations for both Japanese native speakers and American English native speakers. Furthermore, the following relations were clarified in relation to the influence of noise addition on the mother tongue, phoneme pair, and presented sound pressure.

(Native and non-native)
In American English native speakers, there is a signal-to-noise ratio range that is less susceptible to noise addition in phoneme pairs other than BV, whereas in Japanese native speakers, the correct answer rate tends to decrease with slight noise addition. It has been shown.

  In addition, the influence of the noise type may differ depending on the native language of the experiment participant (example: comparison between AE-15 dB condition and JA-9 dB condition of RL conflict). This suggests that the acoustic features used for perception differed depending on the mother tongue.

(Phoneme pair)
The effect of noise was different depending on the phoneme pair. The RL conflict was relatively resistant to the noise used in the actual sapon, but the BV conflict was greatly affected by the addition of a small amount of noise, and the correct answer rate decreased at an almost constant rate in the STH conflict. This indicates that the acoustic features used for the discrimination are different depending on the phoneme pair, and even when the same noise is added, different effects are exerted.

(Present sound pressure)
In Japanese native speakers and American English native speakers, the correct answer rate decreases due to a decrease in the presented sound pressure in a phoneme with BV conflict, and perception is hindered. However, the correct answer rate of RL and STH decreases only for Japanese native speakers due to a decrease in the sound pressure presented.

  From the above results, in FIGS. 1 to 6, the / b / and / v / pair of plosives has been described as an example of the phoneme conflict, but for phonemes that need to be amplified due to other phoneme conflicts, It can be seen that when the phoneme portion is selectively extracted and amplified, the degree of perception improves at least for a speaker having a certain native language.

  Also, for example, it has been clarified as a result of the above experiment that a perception error tends to occur if the burst spectrum cannot be perceived properly. Furthermore, even in the Japanese-only range, for example, “pa” “ta” “ka” is discriminated by the frequency characteristics of the burst spectrum that requires delicate perception, so by using the speech processing device of the present invention, In the case of voice communication between Japanese speakers as well as between English speakers and Japanese speakers, improvement in clarity is also expected.

  The embodiment disclosed this time should be considered as illustrative in all points and not restrictive. The scope of the present invention is defined by the terms of the claims, rather than the description above, and is intended to include any modifications within the scope and meaning equivalent to the terms of the claims.

It is a conceptual diagram which shows an example of the communication system 1000 using the audio | voice processing apparatus of this invention. It is a figure which shows the hardware constitutions of the computer 100 in a block diagram format. It is a figure which shows the structure of the computer 100 which functions as a voice processing apparatus of this invention with a functional block. FIG. 4 is a block diagram for explaining the operations of the frequency analysis unit 1202 and the clarification processing unit 1204 described in FIG. 3 in more detail. It is a figure which shows an example of the audio | voice waveform input from the microphone 132. FIG. It is a figure which shows the result of having frequency-analyzed the waveform, and the result of having selectively amplified. It is a figure which shows the S / N ratio used as experiment conditions. It is a figure which shows the result of the noise addition voice session in JA experiment. It is a figure which shows the result of the sound pressure fluctuation | variation session in JA experiment. It is a figure which shows the result of the noise addition audio | voice session in each phoneme confrontation in AE experiment. It is a figure which shows the result of the sound pressure fluctuation | variation session in AE experiment.

Explanation of symbols

  100 computer, 102 computer main body, 104 display, 106 FD drive, 108 disk drive, 110 keyboard, 112 mouse, 118 CD-ROM, 120 CPU, 122 memory, 124 hard disk, 128 interface, 132 microphone, 134 speaker, 1000 system, 1202 Frequency analysis unit, 1204 Clarification processing unit.

Claims (4)

A voice processing device,
Storage means for storing emphasis information of phonemes to be emphasized according to user attributes;
Frequency analysis means for frequency analysis of the input audio signal;
Based on the analysis result of the frequency analysis means, phoneme detection means for detecting each phoneme portion,
Emphasis processing means for selectively emphasizing the phonological part according to the detection result of the phonological detection means and the emphasis information;
An audio processing apparatus comprising: an output signal selection unit that synthesizes and outputs the input audio signal and the selectively emphasized portion.   The speech processing apparatus according to claim 1, wherein the phoneme to be emphasized is a plosive phoneme.   The phoneme detection means, based on the analysis result of the frequency analysis means, determines a phoneme corresponding to a plosive sound depending on the presence or absence of a vertical pulse in which a certain level of power exists within a predetermined time from a low frequency band to a high frequency band. The audio processing device according to claim 2, wherein the audio processing device is detected. Further comprising phonological acoustic model storage means for storing the acoustic model;
The speech processing apparatus according to claim 1, wherein the phoneme is detected by likelihood calculation based on the acoustic model for each phoneme.