• Title, Summary, Keyword: Speech Enhancement

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Speech Enhancement Using Microphone Array with MMSE-STSA Estimator Based Post-Processing (MMSE-STSA 추정치에 기반한 후처리를 갖는 마이크로폰 배열을 이용한 음성 개선)

  • Kwon Hong Seok;Son Jong Mok;Bae Keun Sung
    • Proceedings of the KSPS conference
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    • pp.187-190
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    • 2002
  • In this paper, a speech enhancement system using microphone array with MMSE-STSA (Minimum Mean Square Error-Short Time Spectral Amplitude) estimator based post-processing is proposed. Speech enhancement is first carried out by conventional delay-and-sum beamforming (DSB). A new MMSE-STSA estimator is then obtained by refining MMSE-STSA estimators from each microphone, which is applied to the output of conventional DSB to obtain additional speech enhancement. Computer simulation for white and pink noises show that the proposed system is superior to other approaches.

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Single-Channel Non-Causal Speech Enhancement to Suppress Reverberation and Background Noise

  • Song, Myung-Suk;Kang, Hong-Goo
    • The Journal of the Acoustical Society of Korea
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    • v.31 no.8
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    • pp.487-506
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    • 2012
  • This paper proposes a speech enhancement algorithm to improve the speech intelligibility by suppressing both reverberation and background noise. The algorithm adopts a non-causal single-channel minimum variance distortionless response (MVDR) filter to exploit an additional information that is included in the noisy-reverberant signals in subsequent frames. The noisy-reverberant signals are decomposed into the parts of the desired signal and the interference that is not correlated to the desired signal. Then, the filter equation is derived based on the MVDR criterion to minimize the residual interference without bringing speech distortion. The estimation of the correlation parameter, which plays an important role to determine the overall performance of the system, is mathematically derived based on the general statistical reverberation model. Furthermore, the practical implementation methods to estimate sub-parameters required to estimate the correlation parameter are developed. The efficiency of the proposed enhancement algorithm is verified by performance evaluation. From the results, the proposed algorithm achieves significant performance improvement in all studied conditions and shows the superiority especially for the severely noisy and strongly reverberant environment.

Enhancement of Excitation in Low-bit-rate Speech Coders (저 전송률 음성 부호화기를 위한 여기 신호 개선 알고리즘에 관한 연구)

  • 이미숙;김홍국;최승호;김도영
    • Proceedings of the IEEK Conference
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    • pp.57-60
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    • 2003
  • In this paper, we propose a new excitation enhancement technique to improve the speech quality of low bit rate speech coders. The proposed technique is based on a harmonic model and it is employed only in the decoding process of speech coders without any additional bits. We develop the procedure of harmonic model parameters estimation and harmonic generation. and apply the technique to a current state of the art low bit rate speech coder, ITU-T G.729 Annex D. Also its performance is measured by using the ITU-T P.862 PESQ score and compared to those of the phase dispersion filter and the long-term postfilter applied to the decoded excitation. It is shown that the proposed excitation enhancement technique can improve the quality of decoded speech and provide better quality for male speech than other techniques.

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Critical Banded Wavelet Packet-Based Spectral Subtractions for Speech Enhancement (음성신호개선을 위한 임계대역 웨이블렛 패킷 기반의 스펙트럼 차감법)

  • Chang, Sung-Wook;Yang, Sung-Il
    • The Journal of the Acoustical Society of Korea
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    • v.23 no.4E
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    • pp.125-133
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    • 2004
  • In this paper, we propose a critical banded wavelet packet-based spectral subtraction for speech enhancement. Critical banded wavelet packet, which reflects the human auditory system, may lead to minimization of intelligibility loss and quality improvement of the enhanced speech in the spectral domain, when combined with an appropriate spectral subtraction gain function. The proposed method shows better performance than the conventional one in comparative assessments. We also show that, for effective evaluation of enhanced speech, it is essential to consider the characteristics of speech quality measures.

A Speech Enhancement Algorithm based on Human Psychoacoustic Property (심리음향 특성을 이용한 음성 향상 알고리즘)

  • Jeon, Yu-Yong;Lee, Sang-Min
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.59 no.6
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    • pp.1120-1125
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    • 2010
  • In the speech system, for example hearing aid as well as speech communication, speech quality is degraded by environmental noise. In this study, to enhance the speech quality which is degraded by environmental speech, we proposed an algorithm to reduce the noise and reinforce the speech. The minima controlled recursive averaging (MCRA) algorithm is used to estimate the noise spectrum and spectral weighting factor is used to reduce the noise. And partial masking effect which is one of the human hearing properties is introduced to reinforce the speech. Then we compared the waveform, spectrogram, Perceptual Evaluation of Speech Quality (PESQ) and segmental Signal to Noise Ratio (segSNR) between original speech, noisy speech, noise reduced speech and enhanced speech by proposed method. As a result, enhanced speech by proposed method is reinforced in high frequency which is degraded by noise, and PESQ, segSNR is enhanced. It means that the speech quality is enhanced.

Speech Enhancement Based on Feature Compensation for Independently Applying to Different Types of Speech Recognition Systems (이기종 음성 인식 시스템에 독립적으로 적용 가능한 특징 보상 기반의 음성 향상 기법)

  • Kim, Wooil
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.18 no.10
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    • pp.2367-2374
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    • 2014
  • This paper proposes a speech enhancement method which can be independently applied to different types of speech recognition systems. Feature compensation methods are well known to be effective as a front-end algorithm for robust speech recognition in noisy environments. The feature types and speech model employed by the feature compensation methods should be matched with ones of the speech recognition system for their effectiveness. However, they cannot be successfully employed by the speech recognition with "unknown" specification, such as a commercialized speech recognition engine. In this paper, a speech enhancement method is proposed, which is based on the PCGMM-based feature compensation method. The experimental results show that the proposed method significantly outperforms the conventional front-end algorithms for unknown speech recognition over various background noise conditions.

Robust speech quality enhancement method against background noise and packet loss at voice-over-IP receiver (배경잡음 및 패킷손실에 강인한 voice-over-IP 수신단 기반 음질향상 기법)

  • Kim, Gee Yeun;Kim, Hyoung-Gook
    • The Journal of the Acoustical Society of Korea
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    • v.37 no.6
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    • pp.512-517
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    • 2018
  • Improving voice quality is a major concern in telecommunications. In this paper, we propose a robust speech quality enhancement against background noise and packet loss at VoIP (Voice-over-IP) receiver. The proposed method combines network jitter estimation based on hybrid Markov chain, adaptive playout scheduling using the estimated jitter, and speech enhancement based on restoration of amplitude and phase to enhance the quality of the speech signal arriving at the VoIP receiver over IP network. The experimental results show that the proposed method removes the background noise added to the speech signal before encoding at the sender side and provides the enhanced speech quality in an unstable network environment.

Method for Spectral Enhancement by Binary Mask for Speech Recognition Enhancement Under Noise Environment (잡음환경에서 음성인식 성능향상을 위한 바이너리 마스크를 이용한 스펙트럼 향상 방법)

  • Choi, Gab-Keun;Kim, Soon-Hyob
    • The Journal of the Acoustical Society of Korea
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    • v.29 no.7
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    • pp.468-474
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    • 2010
  • The major factor that disturbs practical use of speech recognition is distortion by the ambient and channel noises. Generally, the ambient noise drops the performance and restricts places to use. DSR (Distributed Speech Recognition) based speech recognition also has this problem. Various noise cancelling algorithms are applied to solve this problem, but loss of spectrum and remaining noise by incorrect noise estimation at low SNR environments cause drop of recognition rate. This paper proposes methods for speech enhancement. This method uses MMSE-STSA for noise cancelling and ideal binary mask to compensate damaged spectrum. According to experiments at noisy environment (SNR 15 dB ~ 0 dB), the proposed methods showed better spectral results and recognition performance.

Excitation Enhancement Based on a Selective-Band Harmonic Model for Low-Bit-Rate Code-Excited Linear Prediction Coders (저전송률 코드여기 선형 예측 부호화기를 위한 선택적 대역 하모닉 모델 기반 여기신호 개선 알고리즘)

  • Lee, Mi-Suk;Kim, Hong-Kook;Choi, Seung-Ho;Kim, Do-Young
    • Speech Sciences
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    • v.11 no.2
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    • pp.259-269
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    • 2004
  • In this paper, we propose a new excitation enhancement technique to improve the speech quality of low bit-rate code-excited linear prediction (CELP) coders. The proposed technique is based on a harmonic model and it is employed only in the decoding process of speech coders without any additional bits. We develop the procedure of harmonic model parameter estimation and harmonic generation, and apply this technique to a current state-of-the-art low bit rate speech coder, ITU-T G.729 Annex D. Also, its performance is measured by using the ITU-T P.862 PESQ score and compared to those of the phase dispersion filter and the long-term postfilter applied to the decoded excitation. It is shown that the proposed excitation enhancement technique can improve the quality of decoded speech and provide better quality for male speech than other techniques.

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A Selection Method of Reliable Codevectors using Noise Estimation Algorithm (잡음 추정 알고리즘을 이용한 신뢰성 있는 코드벡터 조합의 선정 방법)

  • Jung, Seungmo;Kim, Moo Young
    • Journal of the Institute of Electronics and Information Engineers
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    • v.52 no.7
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    • pp.119-124
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    • 2015
  • Speech enhancement has been required as a preprocessor for a noise robust speech recognition system. Codebook-based Speech Enhancement (CBSE) is highly robust in nonstationary noise environments compared with conventional noise estimation algorithms. However, its performance is severely degraded for the codevector combinations that have lower correlation with the input signal since CBSE depends on the trained codebook information. To overcome this problem, only the reliable codevector combinations are selected to be used to remove the codevector combinations that have lower correlation with input signal. The proposed method produces the improved performance compared to the conventional CBSE in terms of Log-Spectral Distortion (LSD) and Perceptual Evaluation of Speech Quality (PESQ).