• Proceedings of the KSLP Conference
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• 1995.11a
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• pp.154-164
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• 1995

CSL, Model 4300B is a highly flexible audio processing package designed to provide a wide variety of speech analysis operations for both new and sophisticated users. Operations include 1) Data acquisition 2) File management 3) Graphics 4) Numerical display 5) Audio output 6) Signal editing 7) A variety of analysis functions, External module include 1) Input control B) Output control 3) Jacks, Software include 1) Wide range of speech display manipulation 2) Editing 3) Analysis (omitted)

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2004.10a
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• pp.1123-1126
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• 2004

Recognizing emotion in speech is required lots of spoken language corpus not only at the different emotional statues, but also in individual languages. In this paper, we focused on the changes speech signals in different emotions. We compared the features of speech information like formant and pitch according to the 4 emotions (normal, happiness, sadness, anger). In Korean, pitch data on monophthongs changed in each emotion. Therefore we suggested the suitable analysis techniques using these features to recognize emotions in Korean.

• 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.15 no.5
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• pp.5-12
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• 1996

We propose a two-channel(Speech & EGG) pitch detection algorithm. The EGG signal monitors the vibratory motion of vocal folds very well. Therefore, using the EGG signal as well as speech signal, we obtain a reliable and robust pitch detection algorithm that minimizers problems occuring in the pitch detection with speech only. The proposed algorithm gives precise pitch markers that are synchronized to the speech in the time domain. Experimental results demonstrate the superiority of the two-channel pitch detection algorithm over the conventional method, and it can be used in obtaining reference pitch for evaluation of other pitch detection algorithms.

• 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.

• The Journal of the Acoustical Society of Korea
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• v.35 no.1
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• pp.74-82
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• 2016

In this paper, a new automatic speech recognition (ASR) was proposed where ultrasonic doppler signals were used, instead of conventional speech signals. The proposed method has the advantages over the conventional speech/non-speech-based ASR including robustness against acoustic noises and user comfortability associated with usage of the non-contact sensor. In the method proposed herein, 40 kHz ultrasonic signal was radiated toward to the mouth and the reflected ultrasonic signals were then received. Frequency shift caused by the doppler effects was used to implement ASR. The proposed method employed multi-channel ultrasonic signals acquired from the various locations, which is different from the previous method where single channel ultrasonic signal was employed. The PCA(Principal Component Analysis) coefficients were used as the features of ASR in which hidden markov model (HMM) with left-right model was adopted. To verify the feasibility of the proposed ASR, the speech recognition experiment was carried out the 60 Korean isolated words obtained from the six speakers. Moreover, the experiment results showed that the overall word recognition rates were comparable with the conventional speech-based ASR methods and the performance of the proposed method was superior to the conventional signal channel ASR method. Especially, the average recognition rate of 90 % was maintained under the noise environments.

• Proceedings of the KSPS conference
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• 1996.10a
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• pp.435-447
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• 1996

In this paper, we propose the method that extracts the speech feature using the hearing model through signal processing techniques. The proposed method includes the following procedure ; normalization of the short-time speech block by its maximum value, multi-resolution analysis using the discrete wavelet transformation and re-synthesize using the discrete inverse wavelet transformation, differentiation after analysis and synthesis, full wave rectification and integration. In order to verify the performance of the proposed speech feature in the speech recognition task, korean digit recognition experiments were carried out using both the DTW and the VQ-HMM. The results showed that, in the case of using DTW, the recognition rates were 99.79% and 90.33% for speaker-dependent and speaker-independent task respectively and, in the case of using VQ-HMM, the rate were 96.5% and 81.5% respectively. And it indicates that the proposed speech feature has the potential for use as a simple and efficient feature for recognition task

• Phonetics and Speech Sciences
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• v.2 no.2
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• pp.109-115
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• 2010

In this paper, we investigate a signal typing on the basis of visual impression of distinctive spectrogram. Pathological voices are classified into signal type 1, 2, 3, or 4 to estimate perturbation parameters and to mark perceptual rating based on Consensus Auditory-Perceptual Evaluation of Voice (CAPE-V). The results suggest that perturbation analysis can be applied to only type 1 and 2 signals and the perceptual ratings of overall grade increase with each signal type, overall. A good inter-rater reliability is showed among three raters. We recommend that pathological voices should be marked the signal typing and CAPE-V, together, to definitely describe the characteristics of pathological voices.

• Phonetics and Speech Sciences
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• v.8 no.4
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• pp.89-95
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• 2016

The purpose of this work is to analyze and synthesize the pseudo-periodicity of voice using a source model. A speech signal has periodic characteristics; however, it is not completely periodic. While periodicity contributes significantly to the production of prosody, emotional status, etc., pseudo-periodicity contributes to the distinctions between normal and abnormal status, the naturalness of normal speech, etc. Measurement of pseudo-periodicity is typically performed through parameters such as jitter and shimmer. For studying the pseudo-periodic nature of voice in a controlled environment, through collected natural voice, we can only observe the distributions of the parameters, which are limited by the size of collected data. If we can generate voice samples in a controlled manner, experiments that are more diverse can be conducted. In this study, the probability distributions of vowel pitch variation are obtained from the speech signal. Based on the probability distribution of vocal folds, pulses with a designated jitter value are synthesized. Then, the target and re-analyzed jitter values are compared to check the validity of the method. It was found that the jitter synthesis method is useful for normal voice synthesis.

• Speech Sciences
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• v.7 no.1
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• pp.17-29
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• 2000

The STC(Sinusoidal Transform Coding) is a vocoding technique that uses a sinusoidal speech model to obtain high- quality speech at low data rate. It models and synthesizes the speech signal with fundamental frequency and its harmonic elements in frequency domain. To reduce the data rate, it is necessary to represent the sinusoidal amplitudes and phases with as small number of peaks as possible while maintaining the speech quality. As a basic research to develop a low-rate speech coding algorithm using the sinusoidal model, in this paper, we investigate the speech quality depending on the number of sinusoids. By varying the number of spectral peaks from 5 to 40 speech signals are reconstructed, and then their qualities are evaluated using spectral envelope distortion measure and MOS(Mean Opinion Score). Two approaches are used to obtain the spectral peaks: one is a conventional STFT (Short-Time Fourier Transform), and the other is a multiresolutional analysis method.