• Title, Summary, Keyword: Speech analysis

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Microphone Array Based Speech Enhancement Using Independent Vector Analysis (마이크로폰 배열에서 독립벡터분석 기법을 이용한 잡음음성의 음질 개선)

  • Wang, Xingyang;Quan, Xingri;Bae, Keunsung
    • Phonetics and Speech Sciences
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    • v.4 no.4
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    • pp.87-92
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    • 2012
  • Speech enhancement aims to improve speech quality by removing background noise from noisy speech. Independent vector analysis is a type of frequency-domain independent component analysis method that is known to be free from the frequency bin permutation problem in the process of blind source separation from multi-channel inputs. This paper proposed a new method of microphone array based speech enhancement that combines independent vector analysis and beamforming techniques. Independent vector analysis is used to separate speech and noise components from multi-channel noisy speech, and delay-sum beamforming is used to determine the enhanced speech among the separated signals. To verify the effectiveness of the proposed method, experiments for computer simulated multi-channel noisy speech with various signal-to-noise ratios were carried out, and both PESQ and output signal-to-noise ratio were obtained as objective speech quality measures. Experimental results have shown that the proposed method is superior to the conventional microphone array based noise removal approach like GSC beamforming in the speech enhancement.

Application of Shape Analysis Techniques for Improved CASA-Based Speech Separation (CASA 기반 음성분리 성능 향상을 위한 형태 분석 기술의 응용)

  • Lee, Yun-Kyung;Kwon, Oh-Wook
    • MALSORI
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    • no.65
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    • pp.153-168
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    • 2008
  • We propose a new method to apply shape analysis techniques to a computational auditory scene analysis (CASA)-based speech separation system. The conventional CASA-based speech separation system extracts speech signals from a mixture of speech and noise signals. In the proposed method, we complement the missing speech signals by applying the shape analysis techniques such as labelling and distance function. In the speech separation experiment, the proposed method improves signal-to-noise ratio by 6.6 dB. When the proposed method is used as a front-end of speech recognizers, it improves recognition accuracy by 22% for the speech-shaped stationary noise condition and 7.2% for the two-talker noise condition at the target-to-masker ratio than or equal to -3 dB.

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An acoustical analysis of speech of different speaking rates and genders using intonation curve stylization of English (영어의 억양 유형화를 이용한 발화 속도와 남녀 화자에 따른 음향 분석)

  • Yi, So Pae
    • Phonetics and Speech Sciences
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    • v.6 no.4
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    • pp.79-90
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    • 2014
  • An intonation curve stylization was used for an acoustical analysis of English speech. For the analysis, acoustical feature values were extracted from 1,848 utterances produced with normal and fast speech rate by 28 (12 women and 16 men) native speakers of English. Men are found to speak faster than women at normal speech rate but no difference is found between genders at fast speech rate. Analysis of pitch point features has it that fast speech has greater Pt (pitch point movement time), Pr (pitch point pitch range), and Pd (pitch point distance) but smaller Ps (pitch point slope) than normal speech. Men show greater Pt, Pr, and Pd than women. Analysis of sentence level features reveals that fast speech has smaller Sr (sentence level pitch range), Sd (sentence duration), and Max (maximum pitch) but greater Ss (sentence slope) than normal speech. Women show greater Sr, Ss, Sp (pitch difference between the first pitch point and the last), Sd, MaxNr (normalized Max), and MinNr (normalized Min) than men. As speech rate increases, women speak with greater Ss and Sr than men.

Qualitative Classification of Voice Quality of Normal Speech and Derivation of its Correlation with Speech Features (정상 음성의 목소리 특성의 정성적 분류와 음성 특징과의 상관관계 도출)

  • Kim, Jungin;Kwon, Chulhong
    • Phonetics and Speech Sciences
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    • v.6 no.1
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    • pp.71-76
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    • 2014
  • In this paper voice quality of normal speech is qualitatively classified by five components of breathy, creaky, rough, nasal, and thin/thick voice. To determine whether a correlation exists between a subjective measure of voice and an objective measure of voice, each voice is perceptually evaluated using the 1/2/3 scale by speech processing specialists and acoustically analyzed using speech analysis tools such as the Praat, MDVP, and VoiceSauce. The speech parameters include features related to speech source and vocal tract filter. Statistical analysis uses a two-independent-samples non-parametric test. Experimental results show that statistical analysis identified a significant correlation between the speech feature parameters and the components of voice quality.

Feature Parameter Extraction and Analysis in the Wavelet Domain for Discrimination of Music and Speech (음악과 음성 판별을 위한 웨이브렛 영역에서의 특징 파라미터)

  • Kim, Jung-Min;Bae, Keun-Sung
    • MALSORI
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    • no.61
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    • pp.63-74
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    • 2007
  • Discrimination of music and speech from the multimedia signal is an important task in audio coding and broadcast monitoring systems. This paper deals with the problem of feature parameter extraction for discrimination of music and speech. The wavelet transform is a multi-resolution analysis method that is useful for analysis of temporal and spectral properties of non-stationary signals such as speech and audio signals. We propose new feature parameters extracted from the wavelet transformed signal for discrimination of music and speech. First, wavelet coefficients are obtained on the frame-by-frame basis. The analysis frame size is set to 20 ms. A parameter $E_{sum}$ is then defined by adding the difference of magnitude between adjacent wavelet coefficients in each scale. The maximum and minimum values of $E_{sum}$ for period of 2 seconds, which corresponds to the discrimination duration, are used as feature parameters for discrimination of music and speech. To evaluate the performance of the proposed feature parameters for music and speech discrimination, the accuracy of music and speech discrimination is measured for various types of music and speech signals. In the experiment every 2-second data is discriminated as music or speech, and about 93% of music and speech segments have been successfully detected.

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Implementation of Formant Speech Analysis/Synthesis System (포만트 분석/합성 시스템 구현)

  • Lee, Joon-Woo;Son, Ill-Kwon;Bae, Keuo-Sung
    • Speech Sciences
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    • v.1
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    • pp.295-314
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    • 1997
  • In this study, we will implement a flexible formant analysis and synthesis system. In the analysis part, the two-channel (i.e., speech & EGG signals) approach is investigated for accurate estimation of formant information. The EGG signal is used for extracting exact pitch information that is needed for the pitch synchronous LPC analysis and closed phase LPC analysis. In the synthesis part, Klatt formant synthesizer is modified so that the user can change synthesis parameters arbitarily. Experimental results demonstrate the superiority of the two-channel analysis method over the one-channel(speech signal only) method in analysis as well as in synthesis. The implemented system is expected to be very helpful for studing the effects of synthesis parameters on the quality of synthetic speech and for the development of Korean text-to-speech(TTS) system with the formant synthesis method.

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The Optimum Fuzzy Vector Quantizer for Speech Synthesis

  • Lee, Jin-Rhee-;Kim, Hyung-Seuk-;Ko, Nam-kon;Lee, Kwang-Hyung-
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • pp.1321-1325
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    • 1993
  • This paper investigates the use of Fuzzy vector quantizer(FVQ) in speech synthesis. To compress speech data, we employ K-means algorithm to design codebook and then FVQ technique is used to analysize input speech vectors based on the codebook in an analysis part. In FVQ synthesis part, analysis data vectors generated in FVQ analysis is used to synthesize the speech. We have fined that synthesized speech quality depends on Fuzziness values in FVQ, and the optimum fuzziness values maximized synthesized speech SQNR are related with variance values of input speech vectors. This approach is tested on a sentence, and we compare synthesized speech by a convensional VQ with synthesized speech by a FVQ with optimum Fuzziness values.

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A Study on the Endpoint Detection Algorithm (끝점 검출 알고리즘에 관한 연구)

  • 양진우
    • Proceedings of the Acoustical Society of Korea Conference
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    • pp.66-69
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    • 1984
  • This paper is a study on the Endpoint Detection for Korean Speech Recognition. In speech signal process, analysis parameter was classification from Zero Crossing Rate(Z.C.R), Log Energy(L.E), Energy in the predictive error(Ep) and fundamental Korean Speech digits, /영/-/구/ are selected as date for the Recognition of Speech. The main goal of this paper is to develop techniques and system for Speech input ot machine. In order to detect the Endpoint, this paper makes choice of Log Energy(L.E) from various parameters analysis, and the Log Energy is very effective parameter in classifying speech and nonspeech segments. The error rate of 1.43% result from the analysis.

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Pattern Recognition Methods for Emotion Recognition with speech signal

  • Park Chang-Hyun;Sim Kwee-Bo
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • v.6 no.2
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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.

Preliminary study of the perceptual and acoustic analysis on the speech rate of normal adult: Focusing the differences of the speech rate according to the area (정상 성인 말속도의 청지각적/음향학적 평가에 관한 기초 연구: 지역에 따른 말속도 차이를 중심으로)

  • Lee, Hyun-Joung
    • Phonetics and Speech Sciences
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    • v.6 no.3
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    • pp.73-77
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    • 2014
  • The purpose of this study is to investigate the differences of the speech rate according to the area in the perceptual and acoustic analysis. This study examines regional variation in overall speech rate and articulation rate across speaking situations (picture description, free conversation and story retelling) with 14 normal adult (7 in Gyeongnam and 7 in Honam area). The result of an experimental investigation shows that the perceptual speech rate differs significantly between two regional varieties of Koreans with a picture description examined here. A group of Honam speakers spoke significantly faster than a group of Gyeongnam speakers. However, the result of the acoustic analysis shows that the speech rate of the two groups did not differ. And there were significant regional differences in the overall speech rate and articulation rate on the other two speaking situation, free conversation and story retelling. It suggest that we have to study perceptual evaluation with regard to the free conversation and story retelling in future research, and based on the results of this study, a variety of researches on the speech rate will be needed on the various conditions, including various area and SLPs who have wider background and experiences. It is necessary for SLPs to train and experience more to assess patients properly and reliably.