• Journal of Korea Society of Digital Industry and Information Management
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• v.10 no.1
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• pp.131-138
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• 2014

This paper is on a stereo acoustic echo canceller with the blind signal separation for post processing. The convergence speed of the stereo acoustic echo canceller is deteriorated due to mixing two residual signals which are update signals of each echo canceller. To solve this problem, we are to use the blind signal separation(BSS) method separating the mixed signals after the echo cancellers. The blind signal separation method can extracts the source signals by means of the iterative computations with two input signals. We had verified performances of the proposed acoustic echo canceller for stereo through simulations. The results of simulations show that the acoustic echo canceller for stereo using this algorithm operates stably without divergence in the normal state. And, when the speech signals were inputted, this echo canceller achieved about 2dB higher ERLE with the BSS post processing method than without this method. This stereo echo canceller showed the best performance in the case of inputting the real voice signal.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.4 no.2
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• pp.77-82
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• 2011

In this paper, we investigate source separation algorithms for stereo audio mixed using amplitude panning method. This source separation algorithms can be used in various applications such as up-mixing, speech enhancement, and high quality sound source separation. The methods in this paper estimate the panning angles of individual signals using the principal component analysis being applied in time-frequency tiles of the input signal and independently extract each signal through directional filtering. Performances of the methods were evaluated through computer simulations.

• Journal of Korea Society of Digital Industry and Information Management
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• v.8 no.3
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• pp.125-131
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• 2012

This paper is on a stereo acoustic echo canceller with the blind signal separation. The convergence speed of the stereo acoustic echo canceller is deteriorated due to mixing two residual signals in the update signal of each echo canceller. To solve this problem, we are to use the blind signal separation(BSS) method separating the mixed signals. The blind signal separation method can extracts the source signals by means of the iterative computations with two input signals. We had verified performances of the proposed acoustic echo canceller for stereo through simulations. The results of simulations show that the acoustic echo canceller for stereo using this algorithm operates stably without divergence in the normal state. And, when the speech signals were inputted, this echo canceller achieved about 3dB higher ERLE in the case of using the BSS algorithm than the case of not using the BSS algorithm. But this echo canceller didn't get good performances in the case of inputting the white noises as stereo signals.

• ETRI Journal
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• v.36 no.5
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• pp.721-729
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• 2014

We propose a novel phase-based method for single-channel speech enhancement to extract and enhance the desired signals in noisy environments by utilizing the phase information. In the method, a phase-dependent a priori signal-to-noise ratio (SNR) is estimated in the log-mel spectral domain to utilize both the magnitude and phase information of input speech signals. The phase-dependent estimator is incorporated into the conventional magnitude-based decision-directed approach that recursively computes the a priori SNR from noisy speech. Additionally, we reduce the performance degradation owing to the one-frame delay of the estimated phase-dependent a priori SNR by using a minimum mean square error (MMSE)-based and maximum a posteriori (MAP)-based estimator. In our speech enhancement experiments, the proposed phase-dependent a priori SNR estimator is shown to improve the output SNR by 2.6 dB for both the MMSE-based and MAP-based estimator cases as compared to a conventional magnitude-based estimator.

• Proceedings of the Acoustical Society of Korea Conference
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• spring
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• pp.20-23
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• 1999

In this paper, The Split Model Analysis Algorithm, which can generate the wideband speech signal from the spectral information of narrowband signal, is developed. The Split Model Analysis Algorithm deals with the separation of the $10^{th}$ order LPC model into five cascade-connected $2^{nd}$ order model. The use of the less complex $2^{nd}$ order models allows for the exclusion of the complicated nonlinear relationships between model parameters and all the poles of the LPC model. The relationships between the model parameters and its corresponding analog poles is proved and applied to each $2^{nd}$ order model. The wideband speech signal is obtained by changing only the sampling rate

• Proceedings of the IEEK Conference
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• 1999.11a
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• pp.1135-1138
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• 1999

In this paper, The Split Model Analysis Algorithm, which can generate the wideband speech signal from the spectral information of narrowband signal, is developed. The Split Model Analysis Algorithm deals with the separation of the 10$\^$th/ order LPC model into five cascade-connected 2$\^$nd/ order model. The use of the less complex 2$\^$nd/ order models allows for the exclusion of the complicated nonlinear relationships between model parameters and all the poles of the LPC model. The relationships between the model parameters and its corresponding analog poles is proved and applied to each 2$\^$nd/ order model. The wideband speech signal is obtained by changing only the sampling rate.

• Journal of the Korea Computer Industry Society
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• v.5 no.2
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• pp.269-274
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• 2004

Noisy speech recognition is one of most important problems in speech recognition. In this paper, a method which efficiently removes the mixed noise with speech, is proposed. The proposed method is based on the ICA to separate the mixed noise. ICA(Independent component analysis) is a signal processing technique, whose goal is to express a set of random variables as linear combinations of components that are statistically as independent from each other as possible.

• Speech Sciences
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• v.12 no.2
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• pp.29-41
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• 2005

This paper is to show the diphthong system of Jeju dialect speakers in their 70s or more on the basis of the acoustic analysis of their phonetic data. It is revealed through the analysis of their phonetic data that they clearly distinguish such diphthongs as [we], [w$\epsilon$], [yc] and [yo]. However, this paper shows that they are phonetically insensitive to the separation between [ye] and [y$\epsilon$] and they seldom make a precise pronunciation of diphthong [iy], which male speakers tend to pronounce to be [i] and female speakers to be [i].

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2002.11a
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• pp.354.1-354
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• 2002

Pitch is a perception related to frequency, one of the psychological aspects or attributes of tones, and an important factor to determine sound quality of sound together with loudness and timber. while a study on pitch has been actively achieved In the part of speech recognition and speech separation, that for analysis and improvement of product sound quality is not yet enough. (omitted)

• Journal of Digital Convergence
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• v.11 no.10
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• pp.453-458
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• 2013

HMM Speech recognition systems have a few weaknesses, including failure to recognize speech due to the mixing of environment noise other voices. In this paper, we propose a speech feature extraction methode using CHMM for extracting selected target voice from mixture of voices and noises. we make use of channel similarity and correlate relation for the selective speech extraction composes. This proposed method was validated by showing that the average distortion of separation of the technique decreased by 0.430 dB. It was shown that the performance of the selective feature extraction is better than another system.