JPS62191899A - Voiced plosive consonant identification system - Google Patents

Abstract

(57) [Summary] This bulletin contains application data before electronic filing, so abstract data is not recorded.

Description

[Detailed Description of the Invention] [Summary] The present invention relates to a method for identifying voiced plosive consonants from each other, and in order to stably and reliably capture the characteristics of each voiced plosive consonant, the spectrum of the transition part from the point of plosive to the vowel is analyzed. By determining and extracting the analysis position according to the length of time from the plosive point to the vowel rise point and the pitch of the voice signal, it is possible to stably capture hyperphonic part information and detect voiced plosives at a high rate. This allows consonants to be distinguished from each other.

[Industrial application field]

The present invention relates to a speech recognition device, and particularly to a method for distinguishing between voiced plosive consonants.

Speech recognition devices, especially monosyllable recognition devices, can basically consist of all Japanese characters with 68 monosyllables, so they can be used for text input instead of keyboard input, and are currently not being put into practical use as voice word processors. It's getting messy. However, in monosyllable recognition, the word-initial child 1+;l
lυhat'f? The difference in IT shows a great deal of importance,
Speech analysis methods conventionally used for word recognition etc. have the problem of being unable to capture the characteristics of the speech, resulting in low gH, and many more technical problems must be overcome for practical use.

Among these, the problem of identifying consonants within groups whose phonation mechanisms are very similar is particularly difficult, and it is necessary to establish a sophisticated identification method.

[Conventional technology]

Typical conventional methods for identifying voiced plosive consonants include methods that use the spectrum of the plosive part immediately after the point of plosive as a feature, and methods that use the formant locus as a feature. A method using this as an identification parameter has been proposed.

The former is based on the idea that there is information useful for identification in the static spectrum of the fissure, and the latter is based on the formant locus, which is the formant locus, which is the transition start frequency of the second and third formants near the rupture point. The features estimated from the above are used as the feature values.

In addition to the above methods, there are many other methods that use the dynamic characteristics of the transition from the point of rupture to the following vowel. In the method of distinguishing voiced plosive consonants from each other using the characteristics of the transition part of Since phonetic analysis is performed under certain analysis conditions on the vowel side,
Variations in each utterance and variations in the rise of each consonant to the vowel,
Furthermore, there is a problem in that stable analytical results cannot be obtained because the method is strongly affected by pitch fluctuations. .

[Means for solving problems]

FIG. 1 is a block diagram of the principle of the present invention. In the figure, l is a microphone, 2 is an A/D converter, 3 is a rupture point detection section, 10 is an analysis (,2!'fFt21/hole part, 16 is a 17 is a speech analysis section, 18 is a time length calculation section, 19 is an analysis position correction section, and 20 is a short section speech analysis section.

A characteristic component of the present invention is a speech analysis means 17 for extracting a transient spectrum sequence, and this speech analysis means 17 includes means 18 for calculating the time length from the rupture point to the vowel rise point, and means 10 for determining the analysis position of the spectral sequence according to the time length; means 19 for correcting the analysis position in synchronization with the pitch of the audio signal;
and means 20 for performing short-range speech analysis.

[Effect]

In the present invention, by means of calculating the time length from the time of rupture to the time of vowel rise, and means of determining the analysis position of the spectral series according to the time length, it is possible to analyze the fluctuations at each utterance and the vowel of each consonant. The variation in the rise of the sound signal is absorbed by normalizing the time in advance, and furthermore, by providing means for correcting the analysis position in synchronization with the pitch of the audio signal, it functions to reduce the influence of the pitch. It is something to do.

〔Example〕

FIG. 2 is a block diagram of an embodiment of the present invention.

In the figure, 1 is a microphone, 2 is an A/D converter, 3 is a rupture point detection section, 4 is an audio data memory, 5 is an audio power calculation section, 6 is an audio power series memory, 7 is a vowel stationary detection section, 8 1 is a vowel rise detection unit, 9 is a consonant time determination unit, 10 is an analysis position temporary determination unit, a distance calculation unit, 16 is a determination unit, 17 is a speech analysis unit, 18 is a time length calculation unit, and 19 is an analysis position correction unit. Section 20 is a short period speech analysis section.

Figure 3 shows the extraction of the steady mouth of a vowel; the extraction of the 4 starting points and the rising point of the vowel. Figures 1 and 4 are diagrams showing the setting of the temporary analysis position, and Figure 5 is the setting of the actual analysis position. FIG. 6 is a diagram showing extraction of the actual analysis position.

The operation of the embodiment will be explained below.

Discrete monosyllabic speech (voiced plosives) inputted from the microphone 1 is subjected to analog-to-digital conversion by the A/D converter 2 and stored in the speech data memory 4. From the audio signal stored in the memory 4, the rupture time detection section 3 detects the time point at which a rupture, which is a phenomenon peculiar to voiced plosives, occurs, that is, the rupture point. Each υ method is used as this detection method. For example, this can be done by detecting the point in time when the waveform amplitude suddenly changes.

Next, the audio power calculation section 5 calculates the audio power. Assuming that the audio signal stored in the memory 4 is X(1), the audio power is defined as follows (where N is the calculation interval length).

A voice power series is obtained at an analysis period M for the voice signal after the point of rupture detected according to the above definition, and is stored in the voice power series memory 6.

Next, the steady-state starting point of the subsequent -f vowel part is extracted by the vowel steady-state detector 7 based on the speech power temporal sequence.

In the speech power series after the rupture point, the point in time when the power fluctuation becomes less than a certain threshold is defined as the starting point between vowel stationary parts.

If P(Jl) is the time series of voice power, then I P (
l i ) P (l l+ 1 ) l≦TH (threshold value) (2) Let this be one time. (8 points in FIG. 3) Next, the vowel rise detection section 8 detects the vowel rise point. Here, the point in time when the power value is 20 degrees lower than the voice power value at the steady-state starting point of the vowel is determined, and that point is defined as the rising point of the vowel.

(Point T in Figure 3) The interval between the rising point of this vowel and the point of plosive is defined as the consonant interval of the voiced plosive, and the consonant length is determined.

This is found in the consonant part time determination part 9. (See FIG. 3) Next, based on the obtained information, that is, the rupture point, the vowel rise point, and the consonant duration, the analysis position tentative determination section 10 tentatively determines the analysis position. Here, three analysis positions are temporarily determined in the consonant interval. The analysis start position is set at the rupture point, the center of the consonant interval, and the vowel onset point. (Here, as an example, three analysis positions are set, so the consonant length is not actually used. However, for example, if N positions are set, the value obtained by dividing this consonant length by (N-1) is used as the synchronization value. (Set N analysis positions from the point of rupture) (See Figure 4) Next, among the temporarily set analysis positions mentioned above, adjust the waveform phase with respect to two points: the center of the consonant interval and the rise point of the vowel. (Pitch synchronization) Correct the analysis position. This function is executed in the pitch synchronization correction section 11.

Do this as follows.

As shown in Figure 6, there is a distance of about 10m5 around the temporary analysis position.
Apply a check window to the audio signal and detect the maximum point of its amplitude.

This maximum point corresponds to the excitation point of the vocal cords. By this method, the actual analysis position is determined as shown in FIG.

Instructing the analysis position determined by the above method using the analysis position instruction section 12;
Analyze the spectrum using Note that, in order to improve the time resolution, a small window length of several ms is used as the analysis window length.

Obtained input waste vector sequence //I=/I /1 71
The distance calculation between and the standard spectrum series N""f:, f:, j: stored in advance in the dictionary memory 14 is performed based on the distance determination of the following equation.

Distance D-ΣI/'-Door 1... Old... River (3) K
xl j[K This is executed in the distance calculation section 15.

The determination unit 16 generates a result (category with M short distances) based on this distance value.

It is possible to absorb the variation in the rise of each consonant to the vowel in front by making the time regular in advance, and it is also possible to reduce the influence of spectral variation due to pitch, which stabilizes the rapid phenomenon changes of voiced plosive consonants. can be captured in This makes it possible to discriminate between voiced plosive consonants at a high rate.

[Brief explanation of drawings]

Fig. 1 is a block diagram of the principle of the present invention. Fig. 2 is a block diagram of a voiced plosive consonant identification device showing an embodiment of the present invention. Fig. 3 shows extraction of the steady start point of a vowel and the rising point of a vowel. 4 is a diagram showing the setting of a temporary analysis position, FIG. 5 is a diagram showing the setting of the actual analysis position, and FIG. 6 is a diagram showing the extraction of the analysis position of laughter. In FIG. 1, 3 is a rupture point detection unit, 10 is an analysis position provisional determination unit, 16 is a determination unit, 17 is a voice analysis unit, 18 is a time length calculation unit, 19 is an analysis position correction unit, and 20 is a short section audio This is the analysis department. ,y7',,77~'~3, Agent: Patent attorney Teiji Igata, □. Microphone + Full Moon Principle 7゛ Mouth...77 Figure Name 1 Figure Vowel Me Determined Zero Interval Jealous Point 4 Airborne Minute Standing Also 1 Point Extraction No.
3 Fig. ■ 7-Carp and non->5tui beasts Fig. 4 ■ Setting the phase separation position of the carp Fig. 5 Extracting the separating lees of the fruit &

Claims (1)

[Scope of Claims] Means (3) for detecting the point of rupture of a voiced plosive consonant, speech analysis means (17) for extracting a spectral sequence from a speech signal in the transition region from the point of plosive to a vowel, and the spectral sequence. In the voiced plosive consonant identifying device (16) which performs discrimination based on information, the voice analysis means (17) extracts a spectral sequence from the audio signal in the transitional part from the plosive point to the vowel. means (18) for calculating the time length from to the vowel onset point; means (10) for determining the analysis position of the spectral series according to the time length; and correcting the analysis device in synchronization with the pitch of the audio signal. A method for identifying voiced plosive consonants, comprising means (19) for performing short-range speech analysis according to the corrected analysis position.