• 제목/요약/키워드: Cepstral Analysis

검색결과 81건 처리시간 0.028초

일측성 성대마비 환자 평가에서 Cepstral Peak Prominence의 유용성 (Usefulness of Cepstral Peak Prominence (CPP) in Unilateral Vocal Fold Paralysis Dysphonia Evaluation)

  • 이창윤;정희석;손희영
    • 대한후두음성언어의학회지
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    • 제28권2호
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    • pp.84-88
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    • 2017
  • Background and Objectives : The purpose of this study was to compare the usefulness of Cepstral peak prominence (CPP) with parameter of Multiple Dimensional Voice Program (MDVP) in evaluating unilateral vocal fold paraylsis patients with subjective voice impairment. Materials and Methods : From July 2014 to August 2016, 37 patients with unilateral vocal fold paralysis who had been diagnosed with unilateral vocal fold paralysis and had received two or more voice tests before and after the diagnosis were evaluated for maximum phonation time (MPT), MDVP and CPP. Respectively. Voice tests were performed with short vowel /a/ and paragraph reading. Results : The CPP-a (CPP with vowel /a/) and CPP-s (CPP with paragraph reading) of the Cepstrum were statistically negatively correlated with G, R, B, and A before the voice therapy. Jitter, Shimmer, and NHR of MDVP were positively correlated with G, R, B. Jitter, Shimmer, and NHR of the MDVP were significantly correlated with the Cepstrum index. G, B, A and CPP-a and CPP-s showed a statistically significant negative correlation and a somewhat higher correlation coefficient between 0.5 and 0.78. On the other hand, in MDVP index, there was a positive correlation with G and B only with Jitter of 0.4. Conclusion : CPP can be an important evaluation tool in the evaluation of speech in the unilateral vocal cord paralysis when speech energy changes or the cycle is not constant during speech.

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음성 신호 분류에 따른 장애 음성의 변동률 분석, 비선형 동적 분석, 캡스트럼 분석의 유용성 (The Utility of Perturbation, Non-linear dynamic, and Cepstrum measures of dysphonia according to Signal Typing)

  • 최성희;최철희
    • 말소리와 음성과학
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    • 제6권3호
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    • pp.63-72
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    • 2014
  • The current study assessed the utility of acoustic analyses the most commonly used in routine clinical voice assessment including perturbation, nonlinear dynamic analysis, and Spectral/Cepstrum analysis based on signal typing of dysphonic voices and investigated their applicability of clinical acoustic analysis methods. A total of 70 dysphonic voice samples were classified with signal typing using narrowband spectrogram. Traditional parameters of %jitter, %shimmer, and signal-to-noise ratio were calculated for the signals using TF32 and correlation dimension(D2) of nonlinear dynamic parameter and spectral/cepstral measures including mean CPP, CPP_sd, CPPf0, CPPf0_sd, L/H ratio, and L/H ratio_sd were also calculated with ADSV(Analysis of Dysphonia in Speech and VoiceTM). Auditory perceptual analysis was performed by two blinded speech-language pathologists with GRBAS. The results showed that nearly periodic Type 1 signals were all functional dysphonia and Type 4 signals were comprised of neurogenic and organic voice disorders. Only Type 1 voice signals were reliable for perturbation analysis in this study. Significant signal typing-related differences were found in all acoustic and auditory-perceptual measures. SNR, CPP, L/H ratio values for Type 4 were significantly lower than those of other voice signals and significant higher %jitter, %shimmer were observed in Type 4 voice signals(p<.001). Additionally, with increase of signal type, D2 values significantly increased and more complex and nonlinear patterns were represented. Nevertheless, voice signals with highly noise component associated with breathiness were not able to obtain D2. In particular, CPP, was highly sensitive with voice quality 'G', 'R', 'B' than any other acoustic measures. Thus, Spectral and cepstral analyses may be applied for more severe dysphonic voices such as Type 4 signals and CPP can be more accurate and predictive acoustic marker in measuring voice quality and severity in dysphonia.

유도전동기의 고장 진단을 위한 효과적인 특징 추출 방법 (An Effective Feature Extraction Method for Fault Diagnosis of Induction Motors)

  • 흥 뉘엔;김종면
    • 한국컴퓨터정보학회논문지
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    • 제18권7호
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    • pp.23-35
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    • 2013
  • 본 논문은 고장 분류 시스템을 위해 진동 신호로부터 특징 벡터를 자동적으로 추출하는 효과적인 기법을 제안한다. 기존의 멜-주파수 캡스트럼 계수는 진동신호의 노이즈에 민감하여 분류 정확도를 감소시키는 단점이 있다. 이러한 문제를 해결하기 위해 본 논문은 4단계 필터 뱅크로 구성된 스펙트럴 엔벨로프 캡스트럼 계수 분석을 제안하며, 4단계는 (1) 모든 진동 신호의 스펙트럴 엔벨로프를 기술하기 위한 선형 예측 코딩 알고리즘 사용 단계, (2) 일반적인 스펙트럴 모양을 얻기 위해 모든 엔벨로프의 평균화 단계, (3) 평균 엔벨로프와 그 주파수의 최대값을 찾기 위한 기울기 하강 방법 사용 단계, (4) 엔벨로프의 주파수 사이의 거리로부터 계산된 중앙값을 얻는데 사용되는 비 중첩 필터 뱅크 단계로 구성된다. 이4-단계필터뱅크는 특징벡터를 추출하기위해 캡스트럼 계수 계산에 사용된다. 마지막으로 유도전동기의 결함 형태를 구분하기 위해 이러한 특수 파라미터를 사용하는 다중 계층 서포트 벡터 머신을 사용한다. 모의실험 결과, 제안하는 방법은 약 99.65%의 분류 성능을 보이며, 동시에 기존 방법들보다 우수한 성능을 보인다.

잡음에 강한 특징 벡터 및 스펙트럼 차감법을 이용한 음성 인식 (Speech Recognition Using Noise Robust Features and Spectral Subtraction)

  • 신원호;양태영;김원구;윤대희;서영주
    • 한국음향학회지
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    • 제15권5호
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    • pp.38-43
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    • 1996
  • 본 논문에서는 잡음 및 주변 환경에 강인한 것으로 알려져 있는 특징 벡터들을 이용한 인식 성능을 비교하였다. 아울러 스펙트럼 차감법을 적용하여 높은 인식 성능을 얻도록 하였다. 본 논문에서는 환경 변화에 강인한 인식 성능을 얻기 위하여 SMC(Short time Modified Coherence) 분석, 루트(root) 켑스트럼 분석, LDA(Linear Discriminant Analysis), PLP(Perceptual Linear Prediction), RASTA(RelAtive SpecTrAl) 처리 등을 이용하여 인식 실험을 수행하였다. 실험을 위하여 반연속 HMM을 이용한 단독음 인식 시스템을 구현하였고 전시장 및 컴퓨터실의 잡음을 첨가하여 0, 10 및 20dB의 SNR에 대한 인식 실험을 수행하였다. 실험 결과, LPCC(Linear Prediction Cepstral Coefficient)를 이용한 경우에 비하여 SMC나 루트처리를 이용한 멜 켑스트럼(루트_멜 켑스트럼)을 이용한 경우 10dB의 SNR에서 각각 9.86%, 12.68% 향상된 가장 좋은 인식률을 얻었다. 또한 멜 켑스트럼과 루트_멜 켑스트럼을 스펙트럼 차감법과 결합하여 잡음을 제거한 경우 10dB에서 각각 16.7%, 8.4% 향상된 94.91%, 94.28%의 인식률을 얻을 수 있었다.

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TMS320C6201 DSP를 이용한 HMM 기반의 음성인식기 구현 (Implementation of HMM Based Speech Recognizer with Medium Vocabulary Size Using TMS320C6201 DSP)

  • 정성윤;손종목;배건성
    • The Journal of the Acoustical Society of Korea
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    • 제25권1E호
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    • pp.20-24
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    • 2006
  • In this paper, we focused on the real time implementation of a speech recognition system with medium size of vocabulary considering its application to a mobile phone. First, we developed the PC based variable vocabulary word recognizer having the size of program memory and total acoustic models as small as possible. To reduce the memory size of acoustic models, linear discriminant analysis and phonetic tied mixture were applied in the feature selection process and training HMMs, respectively. In addition, state based Gaussian selection method with the real time cepstral normalization was used for reduction of computational load and robust recognition. Then, we verified the real-time operation of the implemented recognition system on the TMS320C6201 EVM board. The implemented recognition system uses memory size of about 610 kbytes including both program memory and data memory. The recognition rate was 95.86% for ETRI 445DB, and 96.4%, 97.92%, 87.04% for three kinds of name databases collected through the mobile phones.

연결발화에서 마비말화자의 음질 특성 (Voice Quality of Dysarthric Speakers in Connected Speech)

  • 서인효;성철재
    • 말소리와 음성과학
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    • 제5권4호
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    • pp.33-41
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    • 2013
  • This study investigated the perceptual and cepstral/spectral characteristics of phonation and their relationships in dysarthria in connected speech. Twenty-two participants were divided into two groups; the eleven dysarthric speakers were paired with matching age and gender healthy control participants. A perceptual evaluation was performed by three speech pathologists using the GRBAS scale to measure the cepstrual/spectral characteristics of phonation between the two groups' connected speech. Correlations showed dysarthric speakers scored significantly worse (with a higher rating) with severities in G (overall dysphonia grade), B (breathiness), and S (strain), while the smoothed prominence of the cepstral peak (CPPs) was significantly lower. The CPPs were significantly correlated with the perceptual ratings, including G, B, and S. The utility of CPPs is supported by its high relationship with perceptually rated dysphonia severity in dysarthric speakers. The receiver operating characteristic (ROC) analysis showed that the threshold of 5.08 dB for the CPPs achieved a good classification for dysarthria, with 63.6% sensitivity and the perfect specificity (100%). Those results indicate the CPPs reliably distinguished between healthy controls and dysarthric speakers. However, the CPP frequency (CPP F0) and low-high spectral ratio (L/H ratio) were not significantly different between the two groups.

MFCC-HMM-GMM을 이용한 근전도(EMG)신호 패턴인식의 성능 개선 (Performance Improvement of EMG-Pattern Recognition Using MFCC-HMM-GMM)

  • 최흥호;김정호;권장우
    • 대한의용생체공학회:의공학회지
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    • 제27권5호
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    • pp.237-244
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    • 2006
  • This study proposes an approach to the performance improvement of EMG(Electromyogram) pattern recognition. MFCC(Mel-Frequency Cepstral Coefficients)'s approach is molded after the characteristics of the human hearing organ. While it supplies the most typical feature in frequency domain, it should be reorganized to detect the features in EMG signal. And the dynamic aspects of EMG are important for a task, such as a continuous prosthetic control or various time length EMG signal recognition, which have not been successfully mastered by the most approaches. Thus, this paper proposes reorganized MFCC and HMM-GMM, which is adaptable for the dynamic features of the signal. Moreover, it requires an analysis on the most suitable system setting fur EMG pattern recognition. To meet the requirement, this study balanced the recognition-rate against the error-rates produced by the various settings when loaming based on the EMG data for each motion.

반폐쇄성도훈련이 기능적 실성증 환자의 음성 개선에 미치는 효과 (Effects of Semi-Occluded Vocal Tract Exercise in Patients with Functional Aphonia)

  • 채혜림;김지성;이동욱;최성희
    • 대한후두음성언어의학회지
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    • 제30권1호
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    • pp.48-52
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    • 2019
  • Background and Objectives : Functional aphonia is characterized by incomplete closure of the vocal folds. Semi-occluded vocal tract exercise (SOVTE) allows smoothly vocal folds collision without damage to the vocal folds tissues to produce normal vocal intensity. The purpose of this study is to report the effect of SOVTE in patients with functional aphonia. Materials and Method : Seven patients diagnosed with functional aphonia were treated with 1-3 voice therapy sessions using voiced lip-trill, humming, Lax Vox in SOVTE. To assess the effectiveness of semi-occluded vocal tract exercise, cepstral analysis and auditory perceptual assessment were performed before and after voice therapy. Results : F0 (fundamental frequency), CPP (cepstral peak prominence) and L/H ratio (low/high spectral ratio) were significantly increased, while CPP Standard deviation, L/H ratio Standard deviation were decreased. In addition, 'Grade', 'Breathiness' and 'Asthenia' were significantly decreased in the GRBAS scale after SOVTE (p<0.05). Conclusion : In our study, SOVTE seemed to be effective to elicit voice quickly and promote vocal folds vibration without muscular effort in patients with functional aphonia.

Gender Classification of Speakers Using SVM

  • Han, Sun-Hee;Cho, Kyu-Cheol
    • 한국컴퓨터정보학회논문지
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    • 제27권10호
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    • pp.59-66
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    • 2022
  • 본 논문에서는 음성 데이터에서 특징벡터를 추출한 후 이를 분석하여 화자의 성별을 분류하는 연구를 진행하였다. 본 연구는 고객이 전화 등 음성을 통해 서비스를 요청할 시 요청한 고객의 성별을 자동으로 인식함으로써 직접 듣고 분류하지 않아도 되는 편의성을 제공한다. 학습된 모델을 활용하여 성별을 분류한 후 성별마다 요청 빈도가 높은 서비스를 분석하여 고객 맞춤형 추천 서비스를 제공하는 데에 유용하게 활용할 수 있다. 본 연구는 공백을 제거한 남성 및 여성의 음성 데이터를 기반으로 각각의 데이터에서 MFCC를 통해 특징벡터를 추출한 후 SVM 모델을 활용하여 기계학습을 진행하였다. 학습한 모델을 활용하여 음성 데이터의 성별을 분류한 결과 94%의 성별인식률이 도출되었다.

Glottal flow 신호에서의 향상된 특징추출 및 다중 특징파라미터 결합을 통한 화자인식 성능 향상 (Performance Improvement of Speaker Recognition Using Enhanced Feature Extraction in Glottal Flow Signals and Multiple Feature Parameter Combination)

  • 강지훈;김영일;정상배
    • 한국정보통신학회논문지
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    • 제19권12호
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    • pp.2792-2799
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    • 2015
  • 본 논문에서는 화자 인식의 성능을 개선하기 위해서 glottal flow로부터 source mel-frequency cepstral coefficient (SMFCC), 왜도, 첨도를 추출하여 활용하였다. 일반적으로 glottal flow의 고주파 대역은 응답의 크기가 평탄하므로 미리 정한 차단주파수 미만에 대해서만 SMFCC를 추출한다. 추출된 SMFCC, 왜도, 첨도는 종래의 특징 파라미터와 결합된 후 종래의 화자인식 시스템과 동등한 조건에서의 성능 비교를 위하여 principal component analysis (PCA) 및 linear discriminiat analysis (LDA)를 통한 차원축소가 행해진다. 대용량의 화자인식 실험결과를 통해서 제안된 인식 시스템이 종래의 화자인식 시스템 보다 더 좋은 성능을 나타냄을 확인할 수 있었으며, 특히 가우시안 혼합이 낮을 때 더 높은 성능향상을 나타내었다.