• International Journal of Fuzzy Logic and Intelligent Systems
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• 제6권2호
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• pp.150-154
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• 2006

In this paper, we apply several pattern recognition algorithms to emotion recognition system with speech signal and compare the results. Firstly, we need emotional speech databases. Also, speech features for emotion recognition are determined on the database analysis step. Secondly, recognition algorithms are applied to these speech features. The algorithms we try are artificial neural network, Bayesian learning, Principal Component Analysis, LBG algorithm. Thereafter, the performance gap of these methods is presented on the experiment result section.

• 한국정보통신학회:학술대회논문집
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• 한국정보통신학회 2018년도 추계학술대회
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• pp.431-433
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• 2018

본 논문은 광대역 음성의 음질 향상을 위해 시간 영역에서 인공대역 확장 기술을 사용하여 초광대역 음성신호를 출력하여 사용자에게 개선된 음질의 음성을 제공하는 시스템을 제안한다. 시간 영역에서 소스필터 모델에 기반하여 광대역 여기신호 및 LSP를 추출하고, 각각의 대역폭 확장 알고리즘을 적용였고, 초광대역 여기신호 및 LSP를 추론하여 초광대역 음성신호를 합성한다. 주관적인 테스트를 통해 광대역 음성신호보다 초광대역 음성신호의 음질을 더 선호하는 결과를 도출하였다.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1998년도 하계학술대회 논문집 G
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• pp.2480-2482
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• 1998

In this paper, the implementation of dual rate ADPCM using G.723 16Kbps and 40Kbps speech codec algorithm is handled. For small signals, the low rate 16Kbps coding algorithm shows the same SNR as the high rate 40Kbps coding algorithm, while the low rate 16Kbps coding algorithm shows the lower SNR than the high rate 40Kbps coding algorithm for large signal. To obtain the good trade-off between the data rate and synthesized speech quality, we applied low rate 16Kbps for the small signal and high rate 40Kbps for the large signal. Various threshold values determining the rate are tested for good trade off data rate and speech quality. Also the low pass filter effect of speech input and output devices is simulated at several cut-off frequencies. To simulation result shows the good speech quality at a low rate comparing with 16Kbps & 40Kbps.

• 제어로봇시스템학회논문지
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• 제16권12호
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• pp.1137-1142
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• 2010

This paper studied the speech parameters less affected by the human emotion for the development of the robust speech recognition system. For this purpose, the effect of emotion on the speech recognition system and robust speech parameters of speech recognition system were studied using speech database containing various emotions. In this study, mel-cepstral coefficient, delta-cepstral coefficient, RASTA mel-cepstral coefficient and frequency warped mel-cepstral coefficient were used as feature parameters. And CMS (Cepstral Mean Subtraction) method were used as a signal bias removal technique. Experimental results showed that the HMM based speaker independent word recognizer using vocal tract length normalized mel-cepstral coefficient, its derivatives and CMS as a signal bias removal showed the best performance of 0.78% word error rate. This corresponds to about a 50% word error reduction as compare to the performance of baseline system using mel-cepstral coefficient, its derivatives and CMS.

• 한국통신학회논문지
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• 제21권5호
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• pp.1172-1179
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• 1996

General adaptive noise canceller(ANC) suffers from the misadjustment of adaptive filter weights, because of the gradient-estimate noise at steady state. In this paper, an adaptive noise cancellation algorithm with speech detector which is distinguishing speech from silence and adaptation-transient region is proposed. The speech detector uses property of adaptive prediction-error filter which can filter the highly correlated speech. To detect speech region, estimation error which is the output of the adaptive filter is applied to the adaptive prediction-error filter. When speech signal apears at the input of the adaptive prediction-error filter. The ratio of input and output energy of adaptive prediction-error filter becomes relatively lower. The ratio becomes large when the white noise appears at the input. So the region of speech is detected by the ratio. Sign algorithm is applied at speech region to prevent the weights from perturbing by output speech of ANC. As results of computer simulation, the proposed algorithm improves segmental SNR and SNR up to about 4 dBand 11 dB, respectively.

• 한국통신학회논문지
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• 제33권3C호
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• pp.234-239
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• 2008

For the efficient coding and transmission, the speech signal can be classified into three distinctive classes: voiced, unvoiced, and transition classes. At low bit rate coding below 4 kbit/s, conventional sinusoidal transform coders synthesize speech of high quality for the purely voiced and unvoiced classes, whereas not for the transition class. The transition class including plosive sound and abrupt voiced-onset has the lack of periodicity, thus it is often classified and synthesized as the unvoiced class. In this paper, the efficient algorithm for the transition class detection is proposed, which demonstrates superior detection performance not only for clean speech but for noisy speech. For the detected transition frame, phase information is transmitted instead of magnitude information for speech synthesis. From the listening test, it was shown that the proposed algorithm produces better speech quality than the conventional one.

• 한국음향학회:학술대회논문집
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• 한국음향학회 1995년도 제12회 음성통신 및 신호처리 워크샵 논문집 (SCAS 12권 1호)
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• pp.33-41
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• 1995

We proposed the approach method of neural network for signal processing, especially speech signal processing and reviewed the algorithms for several neural networks which are used for many alppication field in speech processing. Finally, investigated the trends in neural network method through 3 conference jounal and the ASK jounal in 1994.

• 한국음향학회지
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• 제22권6호
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• pp.443-451
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• 2003

코드북 기반의 CELP 부호기는 코드북에 미리 할당된 부호화 비트율에 따라서 여기 신호를 모델링한 후 코드북을 이용하여 음성신호를 합성한다. 따라서 임의의 다양한 비트율을 하나의 부호기에서 지원하지 못하는 단점이 있다. 본 논문에서 제안하는 가변 비트율 부호기는 웨이블렛 변환 (wavelet transform과 1차원 SPIHr (one dimensional SPIHT)를 이용하여 현재 프레임에 할당되는 비트수에 따라서 여기신호를 부호화한다. 또한 CELP 부호기의 경우처럼 특정한 몇 가지 형태로 여기신호(또는 코드북)를 모델링할 필요가 없고, 정확한 피치정보가 없어도 여기신호를 사용자의 요구에 따라 다양한 비트율로 부호화할 수 있다. 그 결과 코드북이 존재하지 않기 때문에 부호기의 복잡도가 낮으며, CELP 기반의 G.729와 G.723.1 부호기와의 음질 비교 결과 동등하거나 나은 결과를 보여준다.

• 한국컴퓨터정보학회논문지
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• 제21권12호
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• pp.131-137
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• 2016

In this paper, the peak finding algorithms corresponding to the Autocorrelation Function (ACF), which are widely exploited for detecting the pitch of voiced signal, are proposed. According to various researchers, it is well known fact that the estimation of fundamental frequency (F0) in speech signal is not only very important task but quite difficult mission. The proposed algorithms, presented in this paper, are implemented by using many characteristics - such as monotonic increasing function - of ACF function. Thus, the proposed algorithms may be able to estimate both reliable and correct the fundamental frequency as long as the autocorrelation function of speech signal is accurate. Since the proposed algorithms may reduce the computational complexity it can be applied to the real-time processing. The speech data, is composed of Korean emotion expressed words, is used for evaluation of their performance. The pitches are measured to compare the performance of proposed algorithms.

• 한국음향학회지
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• 제16권2호
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• pp.36-40
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• 1997

음성신호처리 분야에서 정확한 피치검출은 중요하고 필요하다. 지금까지 제안된 피치검출 알고리즘들은 음성신호의 다양성으로 인해 피치를 정확히 검출하기가 어렵다. 본 논문에서는 PCM과 같은 균일 양자화기의 잔여신호에 대해 음성신호의 기본주기를 검출하는 새로운 피치검출법을 제안하였다. 제안한 방법은 무잡음 음성에 대해 평균 0.25%의 조오율이 그리고 0dB의 SNR에 대해서는 평균 3.39%의 조오율이 나타나는 정확성을 보였다. 또한 음소의 천이영역이나 배경잡음 하에서도 피치검출의 정확도가 개선된 피치검출의 결과를 얻었다.