JP3886483B2 - Acoustic sensor - Google Patents

Description

  The present invention relates to an acoustic sensor for extracting features of a sound signal in voice recognition processing, acoustic signal processing, and the like, and more particularly to an acoustic sensor for detecting the intensity of a sound signal in each frequency band.

  In systems that perform speech recognition, conventionally, the vibration of a microphone that receives a speech signal is converted and amplified into an electrical signal by an amplifier, and then the analog signal is digitized by an A / D converter to obtain a speech digital signal. The voice digital signal is subjected to fast Fourier transform by software on a computer to extract voice characteristics. Such a speech recognition system is disclosed (for example, see Non-Patent Document 1).

  In order to efficiently extract the characteristics of an audio signal, it is necessary to calculate an acoustic spectrum within a time period that allows the audio signal to be considered to be stationary. In the case of an audio signal, it is considered that it can be regarded as a steady state in a time of 10 to 20 msec. Therefore, signal processing such as fast Fourier transform is executed by software on the computer on the audio digital signal included in the time period of 10 to 20 msec.

  As described above, in the conventional speech recognition method, a speech signal including the entire instantaneous band is converted into an electrical signal by the microphone, and A / D conversion is performed to analyze each spectrum of the electrical signal in order to analyze the spectrum of the electrical signal. And the voice digital signal data is compared with data of a specific voice waveform to extract voice features.

By the way, the auditory mechanism and the psychophysical properties of sound are described in detail (for example, see Non-Patent Document 2). This document shows that the scale of the pitch (pitch) of the sound that humans listen to does not correspond linearly to the frequency as a physical quantity, but linearly corresponds to the scale called mel scale. This Mel Scale is a psychological attribute (psychological scale) that expresses the pitch of the sound as expressed in the scale, and is a scale that directly quantifies the frequency interval called the pitch that sounds to humans at equal intervals. Then, the pitch of the sound of 1000 Hz and 40 phones is defined as 1000 mel. A 500-mel sound signal sounds like a 0.5-pitch sound, and a 2000-mel sound signal sounds like a double-pitch sound. This mel scale can be approximated by the following equation (1) using the frequency f [Hz] as a physical quantity. FIG. 7 shows the relationship between the pitch [mel] and the frequency [Hz] in this approximate expression.
mel = (1000 / log2) log (f / 1000 + 1) (1)

  And in order to extract the feature of an audio | voice efficiently, converting the frequency band of an acoustic spectrum into such a mel scale is often performed. This conversion of the acoustic spectrum to the mel scale is usually performed by software on a computer, as in the case of spectrum analysis.

  In addition, as a method for efficiently extracting voice features, the frequency band of an acoustic spectrum is often converted to a bark scale. This Bark scale is a measure corresponding to the loudness of human psychological sound, and shows the frequency bandwidth (this is called the critical bandwidth) that humans can hear in loud sounds of a certain level. Sounds within this critical bandwidth will sound the same even at different frequencies. For example, if a large amount of noise is generated within the critical bandwidth, a scale indicating a frequency band in which the noise and the signal sound cannot be distinguished by human hearing even though the signal sound is different in frequency from the noise. Bark scale.

In the field of audio signal processing, a critical bandwidth that is easy to handle on a computer is required, and the frequency axis of the acoustic spectrum is indicated by a bark scale that defines one critical band as one bark. FIG. 8 shows a numerical relationship between the critical bandwidth and the Bark scale. Further, these critical bandwidth and bark scale can be approximated by the following equations (2) and (3) using the frequency f [kHz] as a physical quantity.
Critical bandwidth: CB [Hz] = 25 + 75 (1 + 1.4f ² ) ^0.69 (2)
Bark Scale: B [Bark]
= 13 tan ^-1 (0.76f) +3.5 tan ^-1 (f / 7.5) (3)

  By the way, it is known to use an engineering function model of the auditory peripheral system in the field of speech recognition, and is described in detail in Non-Patent Document 2. In the engineering function model, frequency spectrum analysis using a band-pass filter group is a pre-processing. For example, in the pre-processing in the Seneff model, which is one of the typical engineering function models, 40 independent in the frequency region of 130 to 6400 Hz. Frequency spectrum analysis is performed by a critical bandwidth filter group having the selected channel. At this time, the frequency band of the acoustic spectrum is converted to a Barks scale. In this model, the output of the model for the input sound stimulus is obtained by computer simulation, and it is shown that it matches well with the physiological data. Therefore, by using such an engineering function model, the speech recognition rate in noise can be improved in automatic speech recognition.

The frequency spectrum analysis and the conversion of the acoustic spectrum to the mel scale by such a critical bandwidth filter group are usually performed by software on a computer, as in the case of spectrum analysis.
IEEE Signal Processing Magazine, Vol.13, No.5, pp.45-57 (1996) Supervised by Shunichi Amari, Seiichi Nakagawa, Kiyohiro Shikano, Yoichi Higashikura “Neuroscience & Technology Series Voice / Hearing and Neural Network Model” (Ohm, 1992)

  In the conventional method of performing fast Fourier transform processing on a digital sound signal by software on a computer and analyzing the spectrum of the sound signal, there is a problem that the calculation amount is enormous and the calculation load is large. Further, when a series of processes for performing fast Fourier transform on the spectrum of an acoustic signal and converting it to a mel scale is performed by software on a computer, the calculation amount is enormous and the calculation load is large. Furthermore, when the spectrum of an acoustic signal is subjected to frequency spectrum analysis using a critical bandwidth filter group and a series of processes for converting to a bark scale is performed by software on a computer, the calculation amount is enormous and the calculation load is large.

  Further, in the conventional method, there is no problem with a voice whose acoustic spectrum does not change with time, such as a vowel, but a sound of a combination of consonants and vowels, for example, “ka, ki, k, In the case of a consonant that first appears and the intensity of the vowel increases over time, such as “K, Ko, Sa, Ta”, or a combination of complex consonants and vowels such as English The following problems arise. Conventionally, voice is recorded instantaneously, and the sound spectrum is analyzed by summing up the acoustic spectrum of all bands divided at regular intervals, so it is difficult to determine at what point it has changed from consonant to vowel As a result, the recognition rate of speech recognition has been lowered. In order to solve this problem, more voice patterns are stored in the computer in advance and applied to one of these voice patterns, but this causes an increase in computational load. ing.

  The present invention has been made in view of such circumstances, and an object thereof is to provide an acoustic sensor capable of performing acoustic signal detection and frequency spectrum analysis at high speed and accurately on one piece of hardware.

  Another object of the present invention is to provide an acoustic sensor capable of performing acoustic signal detection, frequency spectrum analysis, and frequency scale conversion (conversion to Mel scale or Bark scale) at high speed and accurately on one piece of hardware. It is to provide.

An acoustic sensor according to claim 1 includes a receiving portion that receives a sound wave propagating in a medium, a resonance portion having a plurality of rod-like resonators each having a length that resonates at a different specific frequency, and A holding part for holding a resonance part, and a vibration intensity detection part for detecting the vibration intensity of each of the resonators for each specific frequency, and the distance between two adjacent resonators is made different. The resonance frequency bandwidth of each resonator is set to a predetermined value .

The acoustic sensor according to a second aspect is characterized in that, in the first aspect, the resonance frequencies of the plurality of resonators are set so as to be distributed on a mel scale .

Acoustic sensor according to claim 3, Oite to claim 1, the resonance frequency of the plurality of resonators, characterized in that it is set so as to be distributed in the Bark scale.

Acoustic sensor according to claim 4, Oite to claim 1, the resonance frequency of the plurality of resonators is set so as to distributed Bark scale, bandwidth critical bandwidth corresponding to each resonant frequency It is characterized by being.

An acoustic sensor according to a fifth aspect includes a receiving portion that receives a sound wave propagating in a medium, a resonance portion having a plurality of rod-shaped resonators each having a length that resonates at a different specific frequency, A holding portion for holding a resonance portion, and a vibration intensity detection portion for detecting the vibration intensity of each of the resonators for each specific frequency, and the distance between two adjacent resonators is different , the resonance frequency of the plurality of resonators, have been set so as to be distributed in the bark scale, and wherein the bandwidth corresponding to each resonant frequency is a critical band width.

According to a sixth aspect of the present invention, the acoustic sensor according to the second aspect is a music song input microphone for recognizing a music song.

  According to a seventh aspect of the present invention, in any one of the first to fifth aspects, the acoustic sensor is a voice input microphone for recognizing a voice.

  An acoustic sensor according to an eighth aspect is the acoustic sensor according to any one of the first to seventh aspects, wherein the acoustic sensor is formed on a semiconductor substrate.

Acoustic sensor of the present invention has a plurality of resonators of different lengths such that each resonates with a particular frequency, transmitted sound waves propagated through the medium of these resonators, the vibration of each resonator Is detected. Then, the detected vibration amplitude is converted into an electric signal, and the electric signal is input to the integrating means, and the input electric signal is integrated in a period of an arbitrary period. And the integration result is output for every specific frequency for every arbitrary period.

Moreover, acoustic sensors of the present invention, the resonant frequency in each resonator, mathematically rather than being distributed in a linear scale, so as to linearly distributed in the mel scale. Since the correspondence between the actual vibration frequency and the mel scale is determined based on the equation (1) and FIG. 6, the design specifications of each resonator can be easily determined. And the physical quantity equivalent to the spectrum of an acoustic signal is detectable on a mel scale by detecting the vibration in each resonator matched to the mel scale specification, and performing the process similar to the 1st acoustic sensor mentioned above after that.

Moreover, acoustic sensors of the present invention, the resonant frequency in each resonator, mathematically rather than being distributed in a linear scale, while so as to linearly distributed in the Bark scale, the bandwidth of each resonance frequency To be the critical bandwidth. Since the correspondence between the actual vibration frequency and the Bark scale and the cutoff frequency that determines the critical bandwidth are determined based on the equations (2), (3) and FIG. 7, the design specifications of each resonator can be easily set. Can be determined. And by detecting the vibration in each resonator according to the Bark scale specification, and then performing the same processing as the first acoustic sensor described above, the physical quantity corresponding to the spectrum of the acoustic signal has a critical bandwidth. Can be detected on a bark scale.

  In the acoustic sensor of the present invention, since the intensity of sound can be detected for each desired frequency, an acoustic spectrum can be obtained in real time without performing analysis processing. Therefore, compared with the conventional method in which an acoustic signal in the entire band is input and electrically filtered into each frequency band, in the present invention in which the acoustic signal is mechanically decomposed for each frequency in this way, electrical filtering is performed. It becomes unnecessary and the processing speed is increased. Moreover, even if it divides for every fixed time, there is no omission of acoustic data anywhere. In addition, since acoustic data for each frequency is obtained at regular intervals, the transition of the intensity of each frequency can be confirmed over time, for example, it is possible to more accurately determine temporal changes between vowels and consonants. The discrimination rate of voice recognition can be increased.

  As described above, in the acoustic sensor of the present invention, since the sound wave is mechanically decomposed for each frequency band before being converted into an electric signal, an electrical filtering process using conventional software is unnecessary. And the processing speed is increased. Further, it can be easily manufactured on a semiconductor substrate, and the occupied area can be reduced as compared with the conventional system, and the cost can be reduced. Furthermore, since the intensity of sound can be detected for each desired frequency, an acoustic spectrum can be obtained in real time without performing analysis processing, and acoustic data for each frequency can be obtained at regular intervals. The transition of the intensity of each frequency can be confirmed with the passage of time, the temporal change of speech can be determined more accurately, and the speech recognition discrimination rate can be increased.

  In addition, the acoustic sensor of the present invention includes an assembly of a plurality of resonators having resonance frequencies distributed in the mel scale, or an assembly of a plurality of resonators having resonance frequencies distributed in a bark scale and having a critical bandwidth. Therefore, the voice can be recognized in a state approximated to human hearing, and the features of the voice can be efficiently extracted during the voice recognition.

  Hereinafter, the present invention will be specifically described with reference to the drawings showing embodiments thereof.

(First embodiment)
FIG. 1 is a diagram showing an embodiment of an acoustic sensor of the present invention. The acoustic sensor of the present invention includes a sensor main body 2 formed on a semiconductor silicon substrate 1, an electrode 3, and a detection circuit 4 that is a peripheral circuit. The sensor main body 2 is formed of semiconductor silicon, and has a resonance part 21 having a plurality of (6 in the example of FIG. 1) rod-like parts having different lengths, and the resonance part 21 is fixed for resonance. A plate-like holding portion 22 held on the end side, a short rod-like propagation portion 23 erected on one end of the holding portion 22, and a plate-like shape that receives sound waves propagated in the air connected to the propagation portion 23 And a receiving portion 24.

  The resonance portion 21 is a cantilever, and each rod-like portion is a resonator 25 whose length is adjusted so as to resonate at a specific frequency. The plurality of resonators 25 selectively vibrate at a resonance frequency f expressed by the following equation (4).

f = (CHE ^1/2 ) / (L ² ρ ^1/2 ) (4)
C: constant determined experimentally
H: Thickness of each resonator
L: Length of each resonator
E: Young's modulus of material (semiconductor silicon)
ρ: Density of material (semiconductor silicon)

  As can be seen from the above equation (4), by changing the thickness H or length L of the resonator 25, the resonance frequency f can be set to a desired value. In the example shown in FIG. 1, the thickness H of all the resonators 25 is constant, and the length L is set so as to increase sequentially from the left side to the right side, and each resonator 25 has its own resonance frequency. Like to have. Specifically, from the left side to the right side, a high frequency to a low frequency can be handled within a range of about 15 to 20 kHz of the audible band.

  The bandwidth of the resonance frequency of each resonator 25 depends on the interaction with the adjacent resonator 25 in the process in which vibration energy is transmitted through the resonance portion 21. That is, the bandwidth is determined by the structural design value such as the rate of change of the resonance frequency of the adjacent resonators 25, the distance to the adjacent resonators 25, and the viscosity of the gas between the adjacent resonators 25. Although determined, in this example, the bandwidth of the resonance frequency of each resonator 25 is controlled by changing the distance between the adjacent resonators 25.

  FIG. 5 is a graph showing a change in bandwidth (vertical axis) when the distance D (horizontal axis) to the adjacent resonator 25 is changed for a resonator 25 made of single crystal silicon having a resonance frequency of 3 kHz. It is. FIG. 6 is a diagram showing the relationship between the length L, thickness H, width W, and distance D of the resonator 25. The design values of the resonator 25 are length L = 1706 μm, thickness H = 10 μm, and width. W = 80 μm, and the gas between adjacent resonators 25 is air. It can be understood from FIG. 5 that a desired bandwidth can be set by adjusting the distance D to the adjacent resonator 25. Therefore, in consideration of this, in this example, the distance D between the adjacent resonators 25 is determined so that the bandwidth of each resonator 25 becomes the critical bandwidth shown in FIG.

  The sensor body 2 configured as described above is manufactured on the semiconductor silicon substrate 1 using a semiconductor integrated circuit manufacturing technique or a micromachining technique. In such a configuration, when the sound wave is transmitted to the wave receiving part 24, the plate-like wave receiving part 24 vibrates, and the vibration indicating the sound wave propagates to the holding part 22 through the propagation part 23 and is held by this. The rod-like resonators 25 of the resonating portion 21 are transmitted from the left to the right in FIG. 1 while sequentially resonating at their specific frequencies.

An appropriate bias voltage V _bias is applied to the sensor body 2, and is applied to the tip of each resonator 25 of the resonance portion 21 and the electrode 3 formed on the semiconductor silicon substrate 1 at a position facing the tip. The capacitor is configured. The tip of the resonator 25 is a movable electrode whose position moves up and down with the vibration of the resonator 25, while the electrode 3 formed on the semiconductor silicon substrate 1 is a fixed electrode whose position does not move. When the resonator 25 vibrates at each specific frequency, the distance between the two electrodes fluctuates, so that the capacitance of the capacitor changes.

Each electrode 3 is connected to a detection circuit 4 that converts such a capacitance change into a voltage signal, integrates the converted voltage signal within a predetermined time, and outputs the result. Figure 2 is a diagram showing a configuration of the detection circuit 4, the detection circuit 4 includes an operational amplifier 41 for amplifying at amplification ratio corresponding to an impedance ratio between the capacitor C _s and the reference capacity C _f of the capacitor The integration circuit 43 integrates the output signal of the operational amplifier 42 higher than the reference voltage V _ref for a predetermined time, and the sample hold circuit 44 extracts the output signal from the integration circuit 43 and temporarily holds and outputs it. The detection circuit 4 having such a configuration is formed by, for example, a silicon CMOS process.

The operational amplifier 41, the integrating circuit 43 and the sample hold circuit 44 are supplied with clock pulses φ ₀ , φ ₁ and φ ₂ , respectively. The operational amplifier 41, the integrating circuit 43 and the sample hold circuit 44 are synchronized with these clock pulses, respectively. Works. These clock pulses may be supplied from the outside, or may be supplied from a counter circuit formed on the same semiconductor silicon substrate.

  Next, the operation will be described. When the sound wave propagated in the air is transmitted to the wave receiving portion 24 of the sensor body 2, the plate-like wave receiving portion 24 vibrates and the vibration propagates in the sensor body 2. At this time, the sound wave is transmitted from the left side to the right side of FIG. 1 while resonating each resonator 25 of the cantilever whose length becomes longer. Each resonator 25 has a unique resonance frequency, and each resonator 25 resonates when a sound wave having the unique frequency propagates, and its tip portion vibrates up and down. Due to this vibration, the capacitance of the capacitor formed between the tip portion and the electrode 3 changes. Since the sound wave energy is sequentially converted into the vibration energy of the resonator 25 as the sound wave propagates, the sound wave energy is gradually attenuated by such resonance, and the longest resonator 25 (in FIG. 1). When the sound wave reaches the right end), the energy as the sound wave is almost lost and no reflected wave is generated. Therefore, there is no possibility that the reflected wave affects the capacitance change, and an accurate capacitance change that matches the spectrum of the propagated sound wave can be detected.

The obtained capacitance change is sent into the detection circuit 4. FIG. 3 is a diagram showing a timing chart in the detection circuit 4, and shows clock pulses φ ₀ , φ ₁ and φ ₂ supplied to the operational amplifier 41, the integrating circuit 43 and the sample hold circuit 44, respectively. The clock pulse control in this example is turned on at a low level.

First, in the detection circuit 4, the amplification ratio is determined according to the impedance ratio between the capacitance C _{s of} the capacitor obtained by the operational amplifier 41 and the reference capacitance C _f . For example, when the value of 1 / ωC _s with respect to 1 / ωC _f (ω = 2πf, f: frequency) is ½, the obtained voltage signal is doubled. However, since the operational amplifier 41 is an inverting amplifier whose positive input terminal is grounded, the operational phase of the operational amplifier 42 in the next stage is inverted by a factor of 1. The obtained amplified voltage signal is input to the integrating circuit 43. The integrating circuit 43, high amplification voltage signal from the reference voltage V _ref in a predetermined corresponding to the clock pulses phi ₁ time is accumulated, the integrated signal is input to the sample-and-hold circuit 44. The sample hold circuit 44 repeats sampling and holding of the integration signal according to the clock pulse φ ₂ and outputs the integration signal to the outside.

The above processing is performed in parallel for each detection circuit 4 corresponding to each of the resonators 25 having different lengths. Note that the periods of the clock pulses φ ₀ , φ _1, and φ ₂ shown in FIG. 3 are merely examples, and it is a matter of course that the periods of these clock pulses may be set arbitrarily.

  As described above, in the present invention, by checking the output signal of the detection circuit 4 corresponding to the resonator 25 that resonates at a specific frequency, the intensity of the sound at the specific frequency with an arbitrary time period. The change with time can be known. Further, by examining the output signals of the detection circuit 4 corresponding to the plurality of resonators 25, it is possible to know the change over time of the sound intensity for each of the plurality of frequency bands with an arbitrary time period.

FIG. 4 is a diagram showing the relationship of each detection circuit 4 corresponding to a specific frequency. For example, n kinds of resonant frequencies _{f 1, f 2, f 3} , f 4, ..., in the case where each f _n selectively providing the n number of resonators to respond vibrations that each resonant frequency Output signals V ₁ , V ₂ , V ₃ , V ₄ ,..., V _n can be obtained according to the resonance intensity. For example, when the acoustic sensor of the present invention is used as a microphone for speech input for speech recognition, the intensity of the frequency is obtained according to the resonance intensity for each resonance frequency in the audible band, and based on the obtained analysis pattern. Recognize the voice.

If it is desired to obtain the intensity of only a selected frequency of the sound wave, only the output signal of the detection circuit corresponding to the required resonance frequency may be obtained. For example, when obtaining the intensities of the frequencies f ₁ and f ₃ in FIG. 4, the outputs of the other detection circuits 4-2, 4-4,. If 4-2, 4-4,..., 4-n are not provided, necessary output signals V ₁ , V ₃ can be obtained and unnecessary output signals V ₂ , V ₄ ,. _It is sufficient that _n is not obtained. As an example of use of such an acoustic sensor, an abnormal sound input microphone for detecting abnormal sound having a specific frequency or frequencies is suitable.

(Second Embodiment)
Next, a description will be given of a second embodiment in which the resonance frequency in each resonator is linearly distributed on a mel scale, which is a psychological attribute representing the pitch of a sound as represented by a musical scale. Note that the configuration of the acoustic sensor of the second embodiment is the same as the configuration of the first embodiment described above, but in the second embodiment, the resonance frequency in each resonator 25 is expressed mathematically. Instead of being distributed on a linear scale, it is distributed linearly on a mel scale. That is, the resonance frequency of the n number of resonators _{25 f 1, f 2, f} 3, ..., when the f _n,
f ₁ [Hz] = αf ₂ [Hz] = ………… = α ^n-1 f _n [Hz]
Instead of setting
f ₁ [mel] = αf ₂ [mel] = …… == α ⁿ⁻¹ f _n [mel]
Set as follows. Α is a coefficient that can be arbitrarily set.

  The resonance frequency of each resonator 25 is determined by the above equation (4), and the correspondence between the actual vibration frequency and the mel scale is determined based on the above equation (1) and FIG. Therefore, an arbitrary resonance frequency on the mel scale can be easily assigned to each resonator 25. In this example, the thickness H of all the resonators 25 is constant, and the length L is varied to obtain resonance frequencies corresponding to frequencies that are equally spaced on the mel scale.

  Other configurations and operations are the same as those in the first embodiment described above, and thus the description thereof is omitted.

  In the second embodiment, since the resonance frequencies of the resonators 25 are distributed on a mel scale, octave sounds, semitones, and the like that can be heard by the human ear can be selectively recognized in real time. A microphone with a combined frequency characteristic can be manufactured. Since the temporal changes of pitch sounds such as octaves and semitones can be more accurately discriminated, it is effective for speech recognition and abnormal sound detection. A voice input microphone having excellent sound discrimination can be configured.

(Third embodiment)
Next, a description will be given of a third embodiment in which the resonance frequency in each resonator is linearly distributed on a Bark scale, which is a psychological attribute representing the volume of sound. The configuration of the acoustic sensor of the third embodiment is the same as the configuration of the first embodiment described above. However, in the third embodiment, the resonance frequency in each resonator 25 is expressed by a mathematical formula. Instead of being distributed in a linear scale, it is distributed in a bark scale, and the bandwidth of the resonance frequency in each resonator 25 is made to be a critical bandwidth.

  Based on the correspondence between the Bark scale and the actual frequency shown in FIG. 8, the resonance frequency of each resonator 25 is determined. The resonance frequency of each resonator 25 is determined by the above equation (4). In this example, the thickness H of all the resonators 25 is constant, and the length L is made different so that the Bark scale is used. An arbitrary resonance frequency at is assigned to each resonator 25.

  In the third embodiment, since the resonance frequency of each resonator 25 is distributed on a bark scale, it can have a frequency characteristic and a bandwidth suitable for human hearing and is hidden in noise. It is possible to easily select the sound signals that are present, and it is possible to improve the speech recognition discrimination rate in a noisy situation. In addition, a sensor closer to human hearing can be provided.

  Other configurations and operations are the same as those in the first embodiment described above, and thus the description thereof is omitted.

It is a figure which shows embodiment of the acoustic sensor of this invention. It is a figure which shows the structure of the detection circuit in the acoustic sensor of this invention. It is a figure which shows the timing chart of the detection circuit in the acoustic sensor of this invention. It is a figure which shows the relationship of each detection circuit corresponding to a specific frequency. It is a graph which shows the relationship between the distance between resonators, and a bandwidth. It is a figure showing the relationship of the length of the resonator in the acoustic sensor of this invention, thickness, width, and distance. It is a graph which shows the relationship between an actual frequency and a mel scale value. It is a graph which shows the numerical relationship between a critical bandwidth and a Bark scale.

Explanation of symbols

DESCRIPTION OF SYMBOLS 1 Semiconductor silicon substrate 2 Sensor main body 3 Electrode 4 Detection circuit
21 Resonant part
22 Holding part
23 Propagation part
24 Received part
25 Resonator
41, 42 operational amplifier
43 Integration circuit
44 Sample hold circuit

Claims (8)

A receiving portion that receives a sound wave propagating in the medium, a resonance portion having a plurality of rod-like resonators each having a length that resonates at a different specific frequency, and a holding portion that holds the resonance portion; A vibration intensity detection portion for detecting the vibration intensity of each of the resonators for each specific frequency, and by changing the distance between the two adjacent resonators to obtain a resonance frequency band in each resonator. An acoustic sensor characterized in that the width is set to a predetermined value . The acoustic sensor according to claim 1, wherein resonance frequencies of the plurality of resonators are set so as to be distributed on a mel scale . The acoustic sensor according to claim 1, wherein resonance frequencies of the plurality of resonators are set so as to be distributed on a bark scale . 2. The acoustic sensor according to claim 1, wherein resonance frequencies in the plurality of resonators are set to be distributed on a bark scale, and a bandwidth corresponding to each resonance frequency is a critical bandwidth . A receiving portion that receives a sound wave propagating in the medium, a resonance portion having a plurality of rod-like resonators each having a length that resonates at a different specific frequency, and a holding portion that holds the resonance portion; Each of the resonators includes a vibration intensity detecting portion that detects a vibration intensity for each specific frequency, the distance between two adjacent resonators is different, and the resonance frequencies of the plurality of resonators and it is set so as to be distributed in the bark scale, characteristics and be Ruoto sound sensor that the bandwidth corresponding to each resonant frequency is a critical band width. The acoustic sensor according to claim 2 , wherein the acoustic sensor is a music song input microphone for recognizing a music song.   6. The acoustic sensor according to claim 1, wherein the acoustic sensor is a voice input microphone for recognizing voice.   The acoustic sensor according to claim 1, wherein the acoustic sensor is configured on a semiconductor substrate.

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