• 한국음향학회:학술대회논문집
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• 한국음향학회 1994년도 제11회 음성통신 및 신호처리 워크샵 논문집 (SCAS 11권 1호)
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• pp.42-47
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• 1994

A pitch detector is an essential component in a variety of speech processing systems. Besides providing valuable insights into the nature of the exciation source for speech production, the pitch contour of an utterance is useful for recognizing speakers, aids-to-the handicapped, and is required in almost all speech analysis-synthesis system. Because of the importance of the pitch detection, a wide variety algorithms for pitch detection have been proposed in speech procesing literature. Thus, in this paper we discuss th evarious type of pitch detection algorithms which have been proposed until now. Then we provide th eperformance measurements for seven pitch detection algorithms.

• 한국음향학회지
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• 제15권5호
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• pp.5-12
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• 1996

본 연구에서는 음성 및 EGG 신호를 2-채널 피치검출 알고리즘을 제안하였다. 성대의 떨림에 관한 정확한 정보를 얻을 수 있는 EGG 신호를 이용함으로써 음성신호로부터 피치를 검출하고자 할 때 수반되는 문제점들을 최소화 할 수 있으며, EGG 신호의 왜곡 및 불규칙한 변화는 음성신호의 분석을 통해 보완해 줌으로써 시간영역에서 음성신호에 동기된 정확한 피치 marker를 검출하였다. 2-채널 피치검출 알고리즘은 음성신호만을 이용한 일반적인 피치검출 알고리즘에 비해 보다 정확하고 개선된 피치궤적을 얻을 수 있음을 실험을 통해 보였으며, 따라서 새로이 개발되는 피치검출 알고리즘의 객관적인 비교 및 평가에 이용될 수 있다.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2007년도 제38회 하계학술대회
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• pp.1797-1798
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• 2007

In field of voice pathology, diverse statistics extracted form pitch estimation were commonly used to assess voice quality. In this study, we proposed robust pitch detection algorithm which can estimate pitch of pathological voices in benign vocal fold lesions. we also compared our proposed algorithm with three established pitch detection algorithms; autocorrelation, simplified inverse filtering technique, and nonlinear state-space embedding methods. In the database of total pathological voices of 99 and normal voices of 30, an analysis of errors related with pitch detection was evaluated between pathological and normal voices, or among the types of pathological voices. According to the results of pitch errors, gross pitch error showed some increases in cases of pathological voices; especially excessive increase in PDA based on nonlinear time-series. In an analysis of types of pathological voices classified by aperiodicity and the degree of chaos, the more voice has aperiodic and chaotic, the more growth of pitch errors increased. Consequently, it is required to survey the severity of tested voice in order to obtain accurate pitch estimates.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2005년도 ICCAS
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• pp.89-92
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• 2005

Using natural speech commands for controlling a human-robot is an interesting topic in the field of robotics. In this paper, our main focus is on the verification of a speaker who gives a command to decide whether he/she is an authorized person for commanding. Among possible dynamic features of natural speech, pitch period is one of the most important ones for characterizing speech signals and it differs usually from person to person. However, current techniques of pitch detection are still not to a desired level of accuracy and robustness. When the signal is noisy or there are multiple pitch streams, the performance of most techniques degrades. In this paper, we propose a two-level approach for pitch detection which in compare with standard pitch detection algorithms, not only increases accuracy, but also makes the performance more robust to noise. In the first level of the proposed approach we discriminate voiced from unvoiced signals based on a neural classifier that utilizes cepstrum sequences of speech as an input feature set. Voiced signals are then further processed in the second level using a modified standard AMDF-based pitch detection algorithm to determine their pitch periods precisely. The experimental results show that the accuracy of the proposed system is better than those of conventional pitch detection algorithms for speech signals in clean and noisy environments.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2002년도 하계종합학술대회 논문집(4)
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• pp.381-384
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• 2002

In speech signal processing, it Is very important to detect the pitch exactly in speech recognition, synthesis and analysis. but, it is very difficult to pitch detection from speech signal because of formant and transition amplitude affect. therefore, in this paper, we proposed a pitch detection using the spectrum flattening techniques. Spectrum flattening is to eliminate the formant and transition amplitude affect. In time domain, positive center clipping is process in order to emphasize pitch period with a glottal component of removed vocal tract characteristic. And rough formant envelope is computed through peak-fitting spectrum of original speech signal in frequency domain. As a results, well get the flattened harmonics waveform with the algebra difference between spectrum of original speech signal and smoothed formant envelope. After all, we obtain residual signal which is removed vocal tract element The performance was compared with LPC and Cepstrum, ACF 0wing to this algorithm, we have obtained the pitch information improved the accuracy of pitch detection and gross error rate is reduced in voice speech region and in transition region of changing the phoneme.

• 음성과학
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• 제10권2호
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• pp.85-95
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• 2003

In speech signal processing, it is very important to detect the pitch exactly in speech recognition, synthesis and analysis. If we exactly pitch detect in speech signal, in the analysis, we can use the pitch to obtain properly the vocal tract parameter. It can be used to easily change or to maintain the naturalness and intelligibility of quality in speech synthesis and to eliminate the personality for speaker-independence in speech recognition. In this paper, we proposed a new pitch detection algorithm. First, positive center clipping is process by using the incline of speech in order to emphasize pitch period with a glottal component of removed vocal tract characteristic in time domain. And rough formant envelope is computed through peak-fitting spectrum of original speech signal infrequence domain. Using the roughed formant envelope, obtain the smoothed formant envelope through calculate the linear interpolation. As well get the flattened harmonics waveform with the algebra difference between spectrum of original speech signal and smoothed formant envelope. Inverse fast fourier transform (IFFT) compute this flattened harmonics. After all, we obtain Residual signal which is removed vocal tract element. The performance was compared with LPC and Cepstrum, ACF. Owing to this algorithm, we have obtained the pitch information improved the accuracy of pitch detection and gross error rate is reduced in voice speech region and in transition region of changing the phoneme.

• 융합신호처리학회논문지
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• 제7권4호
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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.

• 대한전자공학회논문지
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• 제17권4호
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• pp.38-44
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• 1980

본 논문에서는 peak 검출과 average magnitude difference function (AMDF)방법을 이용해서 음성의 주기를 고속도로 추출하는 방법이 연구되었다. 먼저 입력 음성을 800Hz로 대역폭을 줄인다음 Pitch peak가 될 만한 몇개의 Peak을 검출한다. 그 다음 이들 peak들의 값을 갖고 AMDF를 계산해서 이들 값들 중에서 최소의 AMDF치를 갖는 peak를 원하는 음성주기로 결정을 한다. 이 방법을 사용하여 음성의 주기를 검출하면 타 음성주기 추출방법 보다 훨씬 적은 계산 시간이 소요될 분만 아니라 비교적 정확한 결과를 얻을 수 있다.

• 한국통신학회:학술대회논문집
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• 한국통신학회 1984년도 춘계학술발표회논문집
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• pp.5-8
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• 1984

Several pitch detection algorithms are studied and compared with the standard pitch detector in a terms of some kinds of errors and each of speaders. Various types of errors are defined, and rank the performance of pitch detectors.

• ETRI Journal
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• 제25권1호
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• pp.49-51
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• 2003

Pitch estimation is important in various speech research areas, but when the speech is noisy, accurate pitch estimation with conventional pitch detectors is almost impossible. To solve this problem, we propose a new pitch detection algorithm for noisy speech using a noise whitening technique on the background noise and obtain successful results.