• Title/Summary/Keyword: AMDF

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A High Speed Pitch Extraction Method Based on Peak Detection and AMDF (Peak 검출과 AMDF에 의한 고속도 음성주기 추출방법)

  • 성원용;은종관
    • Journal of the Korean Institute of Telematics and Electronics
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    • v.17 no.4
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    • pp.38-44
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    • 1980
  • We present a high speed pitch estimation algorithm that is based on peak detection and average magnitude difference function (AMDF). A few pitch candidates are first estimated from the low-pass filtered (800 Hz) speech by a peak detection algorithm. AMDF values of the pitch candidatestare then calculated, and the pitch candidate that yields the minimum AMDF value is chosen as the desired pitch period. The new method requires far less computation time than other pitch estimation algorithms, while it yields fairly accurate results.

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A Study of the Pitch Estimation Algorithms of Speech Signal by Using Average Magnitude Difference Function (AMDF) (AMDF 함수를 이용한 음성 신호의 피치 추정 Algorithm들에 관한 연구)

  • So, Shinae;Lee, Kang Hee;You, Kwang-Bock;Lim, Ha-Young;Park, Jisu
    • Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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    • v.7 no.4
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    • pp.235-242
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    • 2017
  • Peaks (or Nulls) finding algorithms for Average Magnitude Difference Function (AMDF) of speech signal are proposed in this paper. Both AMDF and Autocorrelation Function (ACF) are widely used to estimate a pitch of speech signal. It is well known that the estimation of the fundamental requency (F0) for speech signal is not only important but also very difficult. In this paper, two algorithms, are exploited the characteristics of AMDF, are proposed. First, the proposed algorithm which has a Threshold value is applied to the local minima to detect a pitch period. The Other proposed algorithm to estimate a pitch period of speech signal is utilized the relationship between AMDF and ACF. The data in this paper, is recorded by using general commercial device, is composed of Korean emotion expression words. The recorded speech data are applied to two proposed algorithms and tested their performance.

Speech source estimation using AMDF (AMDF를 이용한 화자위치 추정)

  • 송도훈
    • Proceedings of the Acoustical Society of Korea Conference
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    • 1998.06e
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    • pp.193-196
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    • 1998
  • 본 연구에서는 원격 화상회의 시스템 등에서 Camera를 자동적으로 제어하기 위해 화자의 음성신호를 4개의 마이크로폰 배열(Microphone Array)로 수음하여 그 신호에 의해 화자의 위치를 추정한다. 마이크로폰으로 수음한 음성신호의 TDE(Time Delay Estimation)를 계산할 때 그 연산량을 감소시키기 위해 AMDF 알고리즘을 사용한다. 각 마이크로폰 출력신호에 대해 AMDF 알고리즘으로 시간지연을 구하고 DOA(Direction of Arrival)를 계산한다. 그리고 다시 공간 기하계산을 통해 공간내 화자의 위치를 추정한다. 시험 신호로써 음성신호 '아'음을 사용한 수치 시뮬레이션과 반사음이 존재하는 일반 강의실에서 아나운서가 발성하는 음을 사용하여 AMDF 알고리즘을 이용한 화자위치 추정의 정확도를 조사하였다.

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Application of AMDF for Improvement of algorithm in estimation sytem of speech source (음원위치 추정 시스템에서 속도향상을 위한 AMDF의 적용)

  • 송도훈
    • Proceedings of the Acoustical Society of Korea Conference
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    • 1998.06d
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    • pp.64-67
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    • 1998
  • 원격지간 화상회의 시스템에서 화자의 위치에 따른 카메라 제어를 위해서는 마이크로폰 배렬(Microphone Array)로 수음한 음성신호에 대해 각 마이크로폰간의 빠른 지연시간 추정이 요구된다. 본 연구에서는 음원위치 추정을 위한 지연시간(Time delay) 계산을 위해 AMDF(Average Magnitude Difference Function)를 적용하여 연산시간을 단축시키는데 목적을 두고 있다. 기본의 상호상관함수 (Cross-correlation )알고리즘 과 본 연구에서 적용한 AMDF 알고리즘을 비교하기 위해 SNR 10dB 와 20dB 인 200Hz, 500Hz, 1kHz, 2kHz의 정현파 합성신호와 단음절 음성신호에 대해 시뮬레이션을 행하였다. 시뮬레이션 결과 AMDF 알고리즘의 정확한 지연시간 추정을 확인하였다.

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On Detcdting the Steady State Segments of Speech Waveform by using the Normalized AMDF (규준화된 AMDF 이용한 음성파형의안정상태 구간검출)

  • Bae, Myung-Jin;Kim, Ul-Je;Ahn, Sou-Guil
    • The Journal of the Acoustical Society of Korea
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    • v.10 no.3
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    • pp.44-50
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    • 1991
  • To recognize continued speech, it is necessary to segment the connected acoustic signal into phonetic units. In this paper, as a parameter to detect the transition regions in continued speech, we propose a new noramlized AMDF. The suggested parameter represents a change rate of magnitude of speech signals. As comparing this value with the adjactent frames value the state of the frames can be distinguished as a level between the steady state and transient state.

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Pitch Period Detection Algorithm Using Modified AMDF (변형된 AMDF를 이용한 피치 주기 검출 알고리즘)

  • Seo Hyun-Soo;Bae Sang-Bum;Kim Nam-Ho
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.10 no.1
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    • pp.23-28
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    • 2006
  • Pitch period that is a important factor in speech signal processing is used in various applications such as speech recognition, speaker identification, speech analysis and synthesis. So many pitch detection algorithms have been studied until now. AMDF which is one of pitch period detection algorithms chooses the time interval from valley point to valley point as pitch period. In selection of valley point to detect pitch period, complexity of the algorithm is increased. So in this paper we proposed the simple algorithm using rotation transform of AMDF that detects global minimum valley point as pitch period of speech signal and compared it with existing methods through simulation.

A Study on Pitch Period Detection of Speech Signal Using Modified AMDF (변형된 AMDF를 이용한 음성 신호의 피치 주기 검출에 관한 연구)

  • Seo, Hyun-Soo;Bae, Sang-Bum;Kim, Nam-Ho
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • v.9 no.1
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    • pp.515-519
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    • 2005
  • Pitch period that is a important factor in speech signal processing is used in various applications such as speech recognition, speaker identification, speech analysis and synthesis. So many pitch detection algoritms have been studied until now. AMDF which is one of pitch period detection algorithms chooses the time interval from valley point to valley point as pitch period. In selection of valley point to detect pitch period, complexity of the algoritm is increased. So in this paper we proposed the simple algorithm using modified AMDF that detects global minimum valley point as pitch period of speech signal and compared existing methods with it through simulation.

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Performance Evaluation of Novel AMDF-Based Pitch Detection Scheme

  • Kumar, Sandeep
    • ETRI Journal
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    • v.38 no.3
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    • pp.425-434
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    • 2016
  • A novel average magnitude difference function (AMDF)-based pitch detection scheme (PDS) is proposed to achieve better performance in speech quality. A performance evaluation of the proposed PDS is carried out through both a simulation and a real-time implementation of a speech analysis-synthesis system. The parameters used to compare the performance of the proposed PDS with that of PDSs that are based on either a cepstrum, an autocorrelation function (ACF), an AMDF, or circular AMDF (CAMDF) methods are as follows: percentage gross pitch error (%GPE); a subjective listening test; an objective speech quality assessment; a speech intelligibility test; a synthesized speech waveform; computation time; and memory consumption. The proposed PDS results in lower %GPE and better synthesized speech quality and intelligibility for different speech signals as compared to the cepstrum-, ACF-, AMDF-, and CAMDF-based PDSs. The computational time of the proposed PDS is also less than that for the cepstrum-, ACF-, and CAMDF-based PDSs. Moreover, the total memory consumed by the proposed PDS is less than that for the ACF- and cepstrum-based PDSs.

A Study on Pitch Period Detection Algorithm Based on Rotation Transform of AMDF and Threshold

  • Seo, Hyun-Soo;Kim, Nam-Ho
    • Journal of the Institute of Convergence Signal Processing
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    • v.7 no.4
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    • pp.178-183
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    • 2006
  • As a lot of researches on the speech signal processing are performed due to the recent rapid development of the information-communication technology. the pitch period is used as an important element to various speech signal application fields such as the speech recognition. speaker identification. speech analysis. or speech synthesis. A variety of algorithms for the time and the frequency domains related with such pitch period detection have been suggested. One of the pitch detection algorithms for the time domain. AMDF (average magnitude difference function) uses distance between two valley points as the calculated pitch period. However, it has a problem that the algorithm becomes complex in selecting the valley points for the pitch period detection. Therefore, in this paper we proposed the modified AMDF(M-AMDF) algorithm which recognizes the entire minimum valley points as the pitch period of the speech signal by using the rotation transform of AMDF. In addition, a threshold is set to the beginning portion of speech so that it can be used as the selection criteria for the pitch period. Moreover the proposed algorithm is compared with the conventional ones by means of the simulation, and presents better properties than others.

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Pitch Period Detection Algorithm Using Rotation Transform of AMDF (AMDF의 회전변환을 이용한 피치 주기 검출 알고리즘)

  • Seo, Hyun-Soo;Bae, Sang-Bum;Kim, Nam-Ho
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • v.9 no.2
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    • pp.1019-1022
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    • 2005
  • As recent information communication technology is rapidly developed, a lot of researches related to speech signal processing have been processed. So pitch period is applied as important factor to many application fields such as speech recognition, speaker identification, speech analysis and synthesis. Therefore, many algorithms related to pitch detection have been proposed in time domain and frequency domain and AMDF(average magnitude difference function) which is one of pitch detection algorithms in time domain chooses time interval from valley to valley as pitch period. But, in selection of valley point to detect pitch period, complexity of the algorithm is increased. So in this paper we proposed pitch detection algorithm using rotation transform of AMDF, that taking the global minimum valley point as pitch period and established a threshold about the phoneme in beginning portion, to exclude pitch period selection. and compared existing methods with proposed method through simulation.

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