• MALSORI
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• no.33_34
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• pp.57-69
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• 1997

In this paper, 1 will try to examine the aspects of formants, based on the LPC analysis. In this analysis, five Japanese vowels (a, i, u, e, o) will experience two kinds of experiments: vowels in isolated forms, and vowels in carrier sentences. The analysis results of Japanese vowels of the Japanese natives show a peculiar feature that Japanese vowels form respective vowel groups. Each Japanese vowel makes a statistically significant difference. In the Fl analysis of the vowels grouped by the informant's sex, Japanese vowel (a) shows the greatest standard deviation without regard to the informant's sex. In the F2 analysis of Japanese vowels, each vowel has a statistically significant difference. The fact that the male's [u] shows great standard deviation means that there is a great difference of the frontness of the tongue among the Japanese males in articulating [u]. Isolated vowels and carried vowels show statistically little significance between Fl and F2 frequency values. In another contrastive analysis between the isolated vowel group and the carried vowel group, whether a vowel is articulated in isolation or in a sentence appears to have little effect on its formant frequency.

• Journal of Ocean Engineering and Technology
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• v.26 no.4
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• pp.57-63
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• 2012

In this paper, a Bayesian classifier based on PCA (principle component analysis) is proposed to classify underwater transient signals using $16^{th}$ order LPC (linear predictive coding) coefficients as feature vector. The proposed classifier is composed of two steps. The mechanical signals were separated from biological signals in the first step, and then each type of the mechanical signal was recognized in the second step. Three biological transient signals and two mechanical signals were used to conduct experiments. The classification ratios for the feature vectors of biological signals and mechanical signals were 94.75% and 97.23%, respectively, when all 16 order LPC vector were used. In order to determine the effect of underwater noise on the classification performance, underwater ambient noise was added to the test signals and the classification ratio according to SNR (signal-to-noise ratio) was compared by changing dimension of feature vector using PCA. The classification ratios of the biological and mechanical signals under ocean ambient noise at 10dB SNR, were 0.51% and 100% respectively. However, the ratios were changed to 53.07% and 83.14% when the dimension of feature vector was converted to three by applying PCA. For correct, classification, it is required SNR over 10 dB for three dimension feature vector and over 30dB SNR for seven dimension feature vector under ocean ambient noise environment.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.28B no.7
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• pp.548-556
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• 1991

In this paper, Korean spoken continuous digits are ercognized using DHMM(Dynamic Hidden Markov Model) and lexical analysis to provide the base of developing voice dialing system. After segmentation by phoneme unit, it is recognized. This system can be divided into the segmentation section, the design of standard speech section, the recognition section, and the lexical analysis section. In the segmentation section, it is segmented using the ZCR, O order LPC cepstrum, and Ai, parameter of voice speech dectaction, which is changed according to time. In the standard speech design section, 19 phonemes or syllables are trained by DHMM and designed as a standard speech. In the recognition section, phomeme stream are recognized by the Viterbi algorithm.In the lexical decoder section, finally recognized continuous digits are outputed. This experiment shiwed the recognition rate of 85.1% using data spoken 7 times of 21 classes of 7 continuous digits which are combinated all of the occurence, spoken by 10 man.

• Proceedings of the Acoustical Society of Korea Conference
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• 1998.08a
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• pp.339-343
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• 1998

Sinusoidal model 은 음성신호처리의 넓은 분야에 적용되고 있는 방법으로 고음질의 합성음을 생성해 낼 수 있고, 조작이 용이하다는 장점을 가지고 있다. 본 논문에서는 Analysis-by-synthesis/Overlap-add Sinusoidal model 이라는 방법을 이용하여 시간축 변환과 dam성 변환을 수행하였다. 특히 본 논문에서는 음질향상을 위하여 시간축 변환시에는 정적인 구간과 변화하는 구간을 구별하여 서로 다른 시간축 변환비를 이용하였고, 기존의 LPC 방법에 비해 스펙트럼 포락선을 보다 잘 추정하는 Improved Cepstrum을 이용하여 음정변환에 적용하였다. 또 서로 다른 문맥에서 얻어진 음성단위들을 결합할 때 생기는 위상차이를 극복하기 위하여, 기본주파수 성분이 일치하도록 시간축을 이동하여 합성하였다. 실험결과 본 논문에서 적용한 방법들을 통해 기존 방식에 비해 개선된 음질을 얻을 수 있었다.

• Proceedings of the Acoustical Society of Korea Conference
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• 1991.06a
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• pp.67-72
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• 1991

This paper evaluates thequality of synthesized speech by rule using the LPC CD in the objective measure and then compares the result with the subjective analysis. By evaluating the quality of synthesized speech by rule objectively. We have tried to resolve the problems (Evaluation time or size expansion, variables within the analysis results) that arise when the evaluation is done subjectively. Also by comparing intelligibility-the index for the subjective quality evaluation of synthesized speech by rule-with evaluation results obtained using MOS and the objective evaluation. We have proved the validity of the objective analysis and thus provides a guide that would be useful when R&D and marketing of synthesis by rule method is done.

• Speech Sciences
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• v.5 no.1
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• pp.63-80
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• 1999

In this paper, an adaptive method of dividing a speech signal into an initial, a medial and a final sound of the form of utterance utilized by evaluating extreme limits of short term energy and autocorrelation functions. By applying this method into speech signal composed of a consonant, a vowel and a consonant, it was divided into an initial, a medial and a final sound and its feature analysis of sample by LPC were carried out. As a result of spectrum analysis in each period, it was observed that there existed spectrum features of a consonant and a vowel in the initial and medial periods respectively and features of both in a final sound. Also, when all kinds of words were adaptively divided into 3 periods by using the proposed method, it was found that the initial sounds of the same consonant and the medial sounds of the same vowels have the same spectrum characteristics respectively, but the final sound showed different spectrum characteristics even if it had the same consonant as the initial sound.

• The Journal of the Acoustical Society of Korea
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• v.30 no.4
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• pp.190-196
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• 2011

Bandwidth extension is a technique to improve speech quality and intelligibility, extending from 300-3400 Hz narrowband speech to 50-7000 Hz wideband speech. This paper designs an artificial bandwidth extension (ABE) module embedded in the AMR (adaptive multi-rate) decoder, reducing LPC/LSP analysis and algorithm delay of the ABE module. We also introduce a fast search codebook mapping method for ABE, and design a low power BWE technique based on the AMR decoder. The proposed ABE method reduces the computational complexity and the algorithm delay, respectively, by 28 % and 20 msec, compared to the traditional DTE (decode then extend) method. We also introduce a weighted classified codebook mapping method for constructing the spectral envelope of the wideband speech signal.

• The Journal of the Acoustical Society of Korea
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• v.36 no.1
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• pp.70-77
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• 2017

Bandwidth extension is a technique to improve speech quality, intelligibility and naturalness, extending from the 300 ~ 3,400 Hz narrowband speech to the 50 ~ 7,000 Hz wideband speech. In this paper, an Artificial Bandwidth Extension (ABE) module embedded in the Opus audio decoder is designed using the information of narrowband speech to reduce the computational complexity of LPC (Linear Prediction Coding) and LSF (Line Spectral Frequencies) analysis and the algorithm delay of the ABE module. We proposed a spectral envelope extension method using DBN (Deep Belief Network), one of deep learning techniques, and the proposed scheme produces better extended spectrum than the traditional codebook mapping method.

• The Journal of the Acoustical Society of Korea
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• v.35 no.2
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• pp.134-142
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• 2016

In this paper, a method synthesizing speech signal using the 40 kHz ultrasonic signals reflected from the articulatory muscles was introduced and performance was evaluated. When the ultrasound signals are radiated to articulating face, the Doppler effects caused by movements of lips, jaw, and chin observed. The signals that have different frequencies from that of the transmitted signals are found in the received signals. These ADS (Acoustic-Doppler Signals) were used for estimating of the speech parameters in this study. Prior to synthesizing speech signal, a quantitative correlation analysis between ADS and speech signals was carried out on each frequency bin. According to the results, the feasibility of the ADS-based speech synthesis was validated. ADS-to-speech transformation was achieved by the joint Gaussian mixture model-based conversion rules. The experimental results from the 5 subjects showed that filter bank energy and LPC (Linear Predictive Coefficient) cepstrum coefficients are the optimal features for ADS, and speech, respectively. In the subjective evaluation where synthesized speech signals were obtained using the excitation sources extracted from original speech signals, it was confirmed that the ADS-to-speech conversion method yielded 72.2 % average recognition rates.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.62 no.11
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• pp.1598-1603
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• 2013

Recently, researches on analyzing relationship between the state of emotion and musical stimuli are increasing. In many previous works, data sets from all extracted channels are used for pattern classification. But these methods have problems in computational complexity and inaccuracy. This paper proposes a selection of optimal EEG channel to reflect the state of emotion efficiently according to music listening by analyzing stochastic feature vectors. This makes EEG pattern classification relatively simple by reducing the number of dataset to process.