• Journal of the Korean Institute of Telematics and Electronics
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• v.22 no.1
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• pp.14-21
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• 1985

In this paper, a new pitch extraction method, the area comparison method, is proposed. By the speech production model, the area of the first peak on a pitch interval of speech signals is emphasized. By using the above characteristics, this method have more advantages than the others for pitch extraction. The defective decision caused by an impulsive noise is minimized and the pre-filtering is not necessary for this rr ethos, because the integration of signals takes place in the process.

• The Journal of the Acoustical Society of Korea
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• v.27 no.1E
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• pp.11-16
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• 2008

In this paper, a pitch cycle waveform (PCW) is extracted, quantized, and interpolated in a time domain to synthesize high-quality speech at low bit rates. The pre-alignment technique is proposed for the accurate and efficient PCW extraction, which predicts the current PCW position from the previous PCW position assuming that pitch periods evolve slowly. Since the pitch periods are different frame by frame, the original PCW is converted into the fixed-dimension PCW using the dimension-conversion method, and subsequently quantized by code-excited linear predictive (CELP) coding. The excitation signal for the linear predictive coding (LPC) synthesis filter is generated using the time-domain interpolation and interlink of the quantized PCW's. The coder operates at 4.2 kbit/s and 3.2 kbit/s depending on the pitch period. Informal listening test demonstrates the effectiveness of the proposed coding scheme.

• Proceedings of the Acoustical Society of Korea Conference
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• 1994.06a
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• pp.963-970
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• 1994

In speech signal processing, it is very important to detect the pitch exactly. The algorithms for pitch extraction that have been proposed until now are not enough to detect the fine pitch in speech signal. Thus we propose the new algorithm which takes advantage of the G-peak extraction. It is the method to find MZCI(maximum zer-crossing interval) which is defined as cut-off bandwidth rate of LPF (low pass filter)and detect the pitch period of the voiced signals. This algorithm performs robustly with a gross error rate of 3.63% even in 0 dB SNR environment. The gross error rate for clean speech is only 0.18%. Also it is able to process all course with speed.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.13 no.7
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• pp.3188-3193
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• 2012

It is important to search a pitch for vocoder. The major drawback to vocoders is their large computational requirements in searching a pitch and a codebook. In this paper, a simple method is proposed to improve the pitch searching process in the pitch filter almost without degradation of quality. The period of speech signal is emphasized by using Dual Pulse technique, the same type of autocorrelation method, in pitch search. Sometimes the incorrect pitch can be obtained by halving, doubling and trifling, To solve it, before searching a pitch, we estimate energy rate in a frame and compensate envelop of signal with it. By using the proposed algorithm in pitch search, its required computation are reduced and searching pitch is improved.

• The Journal of the Acoustical Society of Korea
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• v.22 no.8
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• pp.717-726
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• 2003

This paper presents the methods that design the Wavelet-based pitch detector for 2,4 kbps Harmonic-CELP Coder, and that achieve the effective waveform interpolation by decision window shape of the transition region, Waveform interpolation coder operates by encoding one pitch-period-sized segment, a prototype segment, of speech for each frame, generate the smooth waveform interpolation between the prototype segments for voiced frame, But, harmonic synthesis of the prototype waveforms between previous frame and current frame occur not only waveform errors but also discontinuity at frame boundary on that case of pitch halving or doubling, In addtion, in transition region since waveform interpolation coder synthesizes the excitation waveform by using overlap-add with triangularity window, therefore, Harmonic-CELP fail to model the instantaneous increasing speech and synthesis waveform linearly increases, First of all, in order to detect the precise pitch period, we use the hybrid 1st pitch detector, and increse the precision by using 2nd ACF-pitch detector, Next, in order to modify excitation window, we detect the onset, offset of frame by GCI, As the result, pitch doubling is removed and pitch error rate is decreased 5.4% in comparison with ACF, and is decreased 2,66% in comparison with wavelet detector, MOS test improve 0.13 at transition region.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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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.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.2 no.2
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• pp.122-126
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• 2002

In this study, we find features of 3 emotions (Happiness, Angry, Surprise) as the fundamental research of emotion recognition. Speech signal with emotion has several elements. That is, voice quality, pitch, formant, speech speed, etc. Until now, most researchers have used the change of pitch or Short-time average power envelope or Mel based speech power coefficients. Of course, pitch is very efficient and informative feature. Thus we used it in this study. As pitch is very sensitive to a delicate emotion, it changes easily whenever a man is at different emotional state. Therefore, we can find the pitch is changed steeply or changed with gentle slope or not changed. And, this paper extracts formant features from speech signal with emotion. Each vowels show that each formant has similar position without big difference. Based on this fact, in the pleasure case, we extract features of laughter. And, with that, we separate laughing for easy work. Also, we find those far the angry and surprise.

• The Journal of the Acoustical Society of Korea
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• v.13 no.5
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• pp.77-82
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• 1994

In speech signal processing, it is very important to detect the pitch exactly. Although various methods for detecting the pitch of speech signals have been developed, it is difficult to exactly extract the pitch for wide range of speakers and various utterances. Thus we propose a new pitch detection algorithm which takes advantage of the G-peak extraction. It is a method to detect the pitch period of the voiced signals by finding MZCI (maximum zero-crossing interval) of the G-peak which is defined as cut-off bandwidth rate of LPF (low pass filter). This algorithm performs robustly with a gross error rate of 3.63% even in 0 dB SNR environement. The gross error rate for clean speech is only 0.18%. Also it is able to process all courses with high speed.

• The Journal of the Acoustical Society of Korea
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• v.16 no.2
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• pp.36-40
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• 1997

In speech signal processing, it is necessary and important to detect exactly the pitch. The algorithms of pitch extraction which have been proposed until now are difficult exactly pitches over wide range speech signals. In this paper, thus, we proposed a new pitch detection algorithm that finds the fundamental period of speech signal in the residual signal quantized by the uniform quantizer as PCM. The proposed method shows little gross error of average 0.25% for clean speech and average 3.39% for SNR of 0dB. It also achieves results of the pitch contours, improving the accuracy of pitch detection in transient phonemes and noise environments.

• Proceedings of the Acoustical Society of Korea Conference
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• 1995.06a
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• pp.123-126
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• 1995

The waveform coding are concerned with simply preserving the wave shape of speech signal through a redundancy reduction process. In the case of speech synthesis, the wave form coding with high quality are mainly used to the synthesis by analysis. However, because the parameters of this coding are not classified as either excitation and vocal tract parameters, it is difficult to applying the waveform coding to the synthesis by rule. In this paper, we proposed a new pitch alteration method that can change the pitch period in waveform coding by using scaling the time-axis and compensating the spectrum. This is a time-frequency domain method that is preserved in the phase components of the waveform and that has a little spectrum distortion with 2.5% and less for 50% pitch change.