• Journal of the Institute of Convergence Signal Processing
• /
• v.7 no.4
• /
• pp.178-183
• /
• 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.

• Proceedings of the KAIS Fall Conference
• /
• 2002.11a
• /
• pp.212-215
• /
• 2002

유성음에서의 피치 측정 알고리즘은 보편적이고 단순하여 구현하기 용이하다. 피치는 간단한 전환을 통해 음정을 구할 수 있다. 이렇게 구한 음정 정보를 이용하여 미디를 이용한 자동반주기의 음정 조절을 가능하게 할 수 있다. 본 연구에서는 쉽게 피치를 구하기 위해 저가의 방식인 AMDF(Average Magnitude Difference Function) 알고리즘을 이용하여 피치를 구하였고 이를 미디 음정 정보로 전환하기 위한 방법을 제안하였다. 이를 이용하면 가수의 음정에 맞게 자동반주기가 음정을 보정하여 음악을 연주하여 줄 수 있다.

• Journal of Biomedical Engineering Research
• /
• v.11 no.1
• /
• pp.75-82
• /
• 1990

The purpose of this study is to help the hearing Impaired's speech training with a visible speech processing system. In brief, this system converts the features of speech signals into graphics on monitor, and adjusts the features of hearing impaired to normal ones. There are formant and pitch in the features used for this system. They are extracted using the digital signal processing such as linear predictive method or AMDF(Average Magnitude Difference Function). In order to effectively train for the hearing impaired's abnormal speech, easilly visible feature has been being studied.

• Speech Sciences
• /
• v.8 no.2
• /
• pp.73-81
• /
• 2001

In this paper, we focus on the real time implementation of the single channel adaptive noise canceller(ANC) by using TMS320C30 EVM board. The implemented single channel adaptive noise canceller is based on a reference paper [1] in which it is simulated by using the recursive average magnitude difference function(AMDF) to get a properly delayed input speech on a sample basis as a reference signal and normalized least mean square(NLMS) algorithm. To certify results of the real time implementation, we measured the processing time of the ANC and enhancement ratio according to various signalto-noise ratios(SNRs). Experimental results demonstrate that the processing time of the speech signal of 32ms length with delay estimation of every 10 samples is about 26.3 ms, and almost the same performance as given in [1] is obtained with the implemented system.

• Proceedings of the Acoustical Society of Korea Conference
• /
• spring
• /
• pp.113-116
• /
• 1999

신호 대 잡음비가 낮은 환경에서 센서 어레이에 입사된 입력 신호 사이의 지연시간 추정(Time Delay Estimation, 이하 TDE)은 높은 분해능이 요구된다. 본 연구에서는 높은 분해능의 TDE를 구하기 위해 상호상관함수(Cross-Correlation)에 평균 차 함수(Average Magnitude Difference function, AMDF)의 역수를 가중한 MCC (Modified Cross-Correlation)알고리즘을 제안한다. 모의신호를 사용한 수치 시뮬레이션 실험으로 종래의 AMDF, Cross-Correlation 알고리즘과 본 연구에서 제안한 MCC 알고리즘의 분해능을 비교 분석하였다 각 알고리즘의 TDE 결과에 대해 STFT(Short Time fourier Transform)에 의한 시간 주파수 해석을 한 결과 MCC알고리즘을 사용하여 TDE 분해능이 향상되었음을 보고한다.

• Journal of the Korean Institute of Telematics and Electronics B
• /
• v.31B no.7
• /
• pp.33-41
• /
• 1994

A single channel adaptive noise canceling (ANC) technique with a recursive time delay estimator (RTDE) is presented for removing effects of additive noise on the speech signal. While the conventional method makes a reference signal for the adaptive filter using the pitch estimated on a frame basis from the input speech, the proposed method makes the reference signal using the delay estimated recursively on a sample-by-sample basis. As the RTDEs, the recursion formulae of autocorrelation function (ACF) and average magnitude difference function (AMDF) are derived. The normalized least mean square (NLMS) and recursive least square (RLS) algorithms are applied for adaptation of filter coefficients. Experimental results with noisy speech demonstrate that the proposed method improves the perceived speech quality as well as the signal-to-noise ratio and cepstral distance when compared with the conventional method.

• Proceedings of the KIEE Conference
• /
• 2004.11c
• /
• pp.459-461
• /
• 2004

This paper presents an implementation of real-time speaker localization using audio-visual information. Four channels of microphone signals are processed to detect vertical as well as horizontal speaker positions. At first short-time average magnitude difference function(AMDF) signals are used to determine whether the microphone signals are human voices or not. And then the orientation and distance information of the sound sources can be obtained through interaural time difference and interaual level differences. Finally visual information by a camera helps get finer tuning of the speaker orientation. Experimental results of the real-time localization system show that the performance improves to 99.6% compared to the rate of 88.8% when only the audio information is used.

• Speech Sciences
• /
• v.11 no.4
• /
• pp.29-42
• /
• 2004

This paper presents an implementation of real-time speaker localization using audio-visual information. Four channels of microphone signals are processed to detect vertical as well as horizontal speaker positions. At first short-time average magnitude difference function(AMDF) signals are used to determine whether the microphone signals are human voices or not. And then the orientation and distance information of the sound sources can be obtained through interaural time difference. Finally visual information by a camera helps get finer tuning of the angles to speaker. Experimental results of the real-time localization system show that the performance improves to 99.6% compared to the rate of 88.8% when only the audio information is used.

• Proceedings of the KOSOMBE Conference
• /
• v.1990 no.05
• /
• pp.57-61
• /
• 1990

The purpose of this study is to help the hearing impaired's speech training with a visible speech processing system. In brief, this system converts the features of speech signals into graphics on monitor, and adjusts the features of hearing impaired to normal ones. There are form ant and pitch in the features used for this system. They are extracted using the digital signal processing such as linear prediotive method or AMDF(Average Magnitude Difference Function). In order to effectively train for the hearing impaired's abnormal speech, easilly visible feature has been being studied.