• 제목/요약/키워드: Speech Signal

검색결과 1,172건 처리시간 0.03초

Evaluation for speech signal based on human sense and signal quality

  • Mekada, Yoshito;Hasegawa, Hiroshi;Kumagai, Takeshi;Kasuga, Masao
    • 한국방송∙미디어공학회:학술대회논문집
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    • 한국방송공학회 1997년도 Proceedings International Workshop on New Video Media Technology
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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.

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Level Crossing과 DPCM을 사용한 유성음/무성음/묵음의 분류 (Voiced/Unvoiced/Silence Classification of Speech Signal by Level Crossing and DPCM)

  • 김진영;성굉모
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 1987년도 전기.전자공학 학술대회 논문집(II)
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    • pp.1615-1618
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    • 1987
  • 시간 영역에서 만들어진 음성신호의 파라미터을 이용하여 주어진 음성신호의 구간이 유성음, 무성음, 혹은 묵음인지를 분류하는 새로운 알고리듬을 제시하였다. 이에 사용한 파라미터은 구간내에서 샘플링된 값의 절대치 합과 일정한 level 이상의 peak의 합(T-peak), T-peak와 절대치 합의 비 그리고, DPCM의 절대치 합들이다. 이를 파라미터를 이용하여 간단히 유성음/무성음/묵음 구간을 분류 할였다. 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 parameters 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.

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독립 성분 분석과 스펙트럼 향상에 의한 잡음 환경에서의 음성인식 (Speech Recognition in Noise Environment by Independent Component Analysis and Spectral Enhancement)

  • 최승호
    • 대한음성학회지:말소리
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    • 제48호
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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.

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음성인식 시스템에서의 원격 음성입력기의 성능평가 (A Performance of a Remote Speech Input Unit in Speech Recognition System)

  • 이광석
    • 한국정보통신학회:학술대회논문집
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    • 한국해양정보통신학회 2009년도 추계학술대회
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    • pp.723-726
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    • 2009
  • 본 연구에서는, 음성인식 시스템에서의 마이크 어레이 기반으로 한 beamforming 방법을 기반으로 음성신호에 대한 에러감소 알고리듬의 성능평가를 위한 시뮬레이션 하였으며 그 성능을 분석하였다. 또한, 마이크 어레이로 부터 취득한 음성신호로 부터 각 채널에 대한 최대 신호대잡음비 구하고 음성신호별로 신호대잡음비를 비교 검토하였다. 음성 인식률은 경우1에서는 54.2%에서 61.4%로, 경우2에서는 더 낮은 신호대잡음비로 41.2%에서 50.5%로 각각 개선됨을 알 수 있었다. 따라서 평균 에러감소율은 경우1에서 15.7%를 보였다.

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A STUDY ON THE SPEECH SYNTHESIS-BY-RULE SYSTEM APPLIED MULTIBAND EXCITATION SIGNAL

  • Kyung, Younjeong;Kim, Geesoon;Lee, Hwangsoo;Lee, Yanghee
    • 한국음향학회:학술대회논문집
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    • 한국음향학회 1994년도 FIFTH WESTERN PACIFIC REGIONAL ACOUSTICS CONFERENCE SEOUL KOREA
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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.

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Improved Leakage Signal Blocking Methods for Two Channel Generalized Sidelobe Canceller

  • Kim, Ki-Hyeon;Ko, Han-Seok
    • 음성과학
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    • 제13권1호
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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.

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성대 신호를 이용한 인식 시스템 (RECOGNITION SYSTEM USING VOCAL-CORD SIGNAL)

  • 조관현;한문성;박준석;정영규
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 2005년도 학술대회 논문집 정보 및 제어부문
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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.

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연속음성신호에서 IMBE 모델을 이용한 SNR 추정 연구 (IMBE Model Based SNR Estimation of Continuous Speech Signals)

  • 박형우;배명진
    • 한국음향학회지
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    • 제29권2호
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    • pp.148-153
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    • 2010
  • 음성 신호처리 환경에서 잡음이 섞인 신호를 개선할 목적으로 음성향상 기법이 많이 이용되고 있다. 잡음추정 알고리즘은 변화하는 환경에 빠르게 적응할 수 있어야 하며 음성신호의 영향을 줄이기 위해 음성신호가 존재하지 않는 구간에서만 잡음의 파워를 갱신한다. 이러한 방법은 음성구간검출이 선행되어야 한다. 그러나 잡음에 열화된 음성신호에 묵음구간이 존재하지 않을 경우, 위와 같이 음성검출을 통한 묵음구간에서의 잡음 추정 방법 및 SNR 추정 방법이 적용될 수 없다. 본 논문에서는 묵읍구간이 존재하지 않는 연속음성신호에서 SNR을 추정하는 기법을 제안한다. 음성신호는 MBE(Multi-Band Excitation) 발성 모델에 따라 유 무성음으로 구분할 수 있다. 그리고 에너지가 유성음에 대부분 분포하기 때문에, 부가성 잡음환경에서 유성음의 에너지를 음성신호의 에너지로 근사화하여 SNR을 추정할 수 있다. 제안하는 방식은 연속음성신호를 IMBE (Improved Multi-Band Exciation) 보코더를 이용해 유 무성음 대역으로 구분하고, 각각 대역의 에너지 정보를 아용하여 단구간 음성신호의 SNR을 계산한다. 전체 음성구간의 SNR은 단구간 SNR의 평균값을 통해 추정한다.

밴드 별 잡음 특징을 이용한 골전도 음성신호의 잡음 제거 알고리즘 (Noise Cancellation Algorithm of Bone Conduction Speech Signal using Feature of Noise in Separated Band)

  • 이지나;이기현;나승대;성기웅;조진호;김명남
    • 한국멀티미디어학회논문지
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    • 제19권2호
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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.

웨이브렛 변환을 이용한 피치검출 (Pitch Detection Using Wavelet Transform)

  • 석종원;손영호;배건성
    • 음성과학
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    • 제5권1호
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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.

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