• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 1997.06a
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• pp.13-18
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• 1997

Each reproducing speech signal has each particular signal property, because of the processing of encoding and decoding for communications through various media. In this paper, we examine the correlation between speech signal quality and sensory pleasure for the sensory improvement of that signal. In experiments, we evaluate the quality of speech signals through various media by psychological auditory test and physical features of these signals.

• Proceedings of the KIEE Conference
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• 1987.07b
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• pp.1615-1618
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• 1987

This paper proposes new algorithm for classifying speech signal frame into voiced, unvoiced, silence frame, using the parameters extracted from time domain behavior of speech signal The prameters used in this paper are absolute magnitude, the sum of peaks lager than reference level (T-peak), the ratio of T-peak to absolute magnitude and the magnitude of signal outputs of DPCM. Using this parameters, speech signal is more easily classified into voiced/ unvoiced/silence frame.

• MALSORI
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• no.48
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• pp.81-91
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• 2003

In this paper, we propose a speech recognition method based on independent component analysis (ICA) and spectral enhancement techniques. While ICA tris to separate speech signal from noisy speech using multiple channels, some noise remains by its algorithmic limitations. Spectral enhancement techniques can compensate for lack of ICA's signal separation ability. From the speech recognition experiments with instantaneous and convolved mixing environments, we show that the proposed approach gives much improved recognition accuracies than conventional methods.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2009.10a
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• pp.723-726
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• 2009

In this research, We simulated performances of error reduction algorithm for the speech signal based on the microphone array-based beamforming method in speech recognition system and analyzed its performance. Also, we processed speech signal adopted from microphone array and maximum signal to noise ratio for each channel, and then compared them with signal to noise ratio of speech signal. Speech recognition rate is improved from 54.2% to 61.4% in case 1 and is improved from 41.2% to 50.5% in case 2 of the lower signal to noise ratio. Therefore the average reduction rates are showed 15.7% in case 1.

• Proceedings of the Acoustical Society of Korea Conference
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• 1994.06a
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• pp.1098-1103
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• 1994

In this paper, we design and implement the Korean speech synthesis by rule system. This system is applied the multiband excitation signal on voiced sounds. The multiband excitation signal is obtained by mixing impluse spectrum and which noise spectrum. We find that the quality of synthesized speech is improved using this application. Also, we classify the voiced sounds by cepstral euclidian distance measure for reducing overhead memory. The representative excitation signal of the same group's voiced sounds is used as excitation signal on synthesis. This method does not affect the quality of synthesized speech. As the result of experiment, this method eliminates the "buzziness" of synthesized speech and reduces the spectral distortion of synthesized speech.ed speech.

• Speech Sciences
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• v.13 no.1
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• pp.117-128
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• 2006

The two-channel Generalized Sidelobe Canceller (GSC) scheme suffers from the presence of leakage signal in the reference channel. The leakage signal is caused by the dissimilar impulse responses between microphones, and different paths from speech source to microphones. Such leakage is detrimental to speech enhancement of the GSC since the desired reference signal becomes corrupted. In order to suppress the signal leakage, two matrix injection methods are proposed. In the first method, a simple gain compensation matrix is used. In the second, a projection matrix for reducing the error between the actual and the ideal primary and reference signals, is used. This paper describes the performance degradation resulting from leakage, and proposes effective methods to resolve the problem. Representative experiments were conducted to demonstrate the effectiveness of the proposed methods on recorded speech and noise in an actual automobile environment.

• Proceedings of the KIEE Conference
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• 2005.10b
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• pp.216-218
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• 2005

This paper present a new approach to a noise robust recognizer for WPS interface. In noisy environments, performance of speech recognition is decreased rapidly. To solve this problem, We propose the recognition system using vocal-cord signal instead of speech. Vocal-cord signal has low quality but it is more robust to environment noise than speech signal. As a result, we obtained 75.21% accuracy using MFCC with CMS and 83.72% accuracy using ZCPA with RASTA.

• The Journal of the Acoustical Society of Korea
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• v.29 no.2
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• pp.148-153
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• 2010

In speech signal processing, speech signal corrupted by noise should be enhanced to improve quality. Usually noise estimation methods need flexibility for variable environment. Noise profile is renewed on silence region to avoid effects of speech properties. So we have to preprocess finding voice region before noise estimation. However, if received signal does not have silence region, we cannot apply that method. In this paper, we proposed SNR estimation method for continuous speech signal. A Speech signal consists of Voice and Unvoiced Band in The MBE excitation model. And the energy of speech signal is mostly distributed on voiced region, so we can estimate SNR by the ratio of voiced region energy to unvoiced. We use the IMBE vocoder for the Voice or Unvoice band of segmented speech signal. Continuously we calculate the segmented SNR using that information and the energy of each band. And we estimate the SNR of continuous speech signal.

• Journal of Korea Multimedia Society
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• v.19 no.2
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• pp.128-137
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• 2016

In mobile communication, air conduction(AC) speech signal had been commonly used, but it was easily affected by ambient noise environment such as emergency, military action and rescue. To overcome the weakness of the AC speech signal, bone conduction(BC) speech signal have been used. The BC speech signal is transmitted through bone vibration, so it is affected less by the background noise. In this paper, we proposed noise cancellation algorithm of the BC speech signal using noise feature of decomposed bands. The proposed algorithm consist of three steps. First, the BC speech signal is divided into 17 bands using perceptual wavelet packet decomposition. Second, threshold is calculated by noise feature during short time of separated-band and compared to absolute average of the signal frame. Therefore, the speech and noise parts are detected. Last, the detected noise parts are removed and then, noise eliminated bands are re-synthesised. In order to confirm the efficiency of the proposed algorithm, we compared the proposed algorithm with conventional algorithm. And the proposed algorithm has better performance than the conventional algorithm.

• Speech Sciences
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• v.5 no.1
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• pp.23-33
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• 1999

Mallat has shown that, with a proper choice of wavelet function, the local maxima of wavelet transformed signal indicate a sharp variation in the signal. Since the glottal closure causes sharp discontinuities in the speech signal, dyadic wavelet transform can be useful for detecting abrupt change in the voiced sounds, i.e., epochs. In this paper, we investigate the glottal closure instants obtained from the wavelet analysis of speech signal and compare them with those obtained from the EGG signal. Then, we detect pitch period of speech signal on the basis of these results. Experimental results demonstrated that local maxima of wavelet transformed signal give accurate estimation of epoch and pitch periods of voiced sound obtained by the proposed algorithm also correspond to those from EGG well.