• Proceedings of the IEEK Conference
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• 2002.06d
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• pp.369-372
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• 2002

In this paper, we present an improved TTS synthesis system using articulatory synthesis and concatenative synthesis. In concatenative synthesis, segments of speech are excised from spoken utterances and connected to form the desired speech signal. We adopt LPC as a parameter, VQ to reduce the memory capacity, and TD-PSOLA to solve the naturalness problem.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.41 no.2
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• pp.209-216
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• 1992

Deafs train articulation by observing mouth of a tutor, sensing tactually the motions of the vocal organs, or using speech training aids. Present speech training aids for deafs can measure only single speech parameter, or display only frequency spectra in histogram of pseudo-color. In this study, a speech training aids that can display subject's articulation in the form of a cross section of the vocal organs and other speech parameters together in a single system is to be developed and this system makes a subject know where to correct. For our objective, first, speech production mechanism is assumed to be AR model in order to estimate articulatory motions of the vocal organs from speech signal. Next, a vocal tract profile model using LP analysis is made up. And using this model, articulatory motions for Korean vowels are estimated and displayed in the vocal tract profile graphics.

• Phonetics and Speech Sciences
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• v.2 no.4
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• pp.185-192
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• 2010

The acoustic vowel space has been used as an acoustic parameter in dysarthric speech. The aim of this work was to examine mathematical formulae for acoustic vowel space and to apply these to Korean speakers with idiopathic Parkinson's disease(IPD). Five acoustic parameters were chosen from earlier works and one new parameter was proposed, the pentagonal vowel space. The six parameters included triangular vowel space (3 area), irregular quadrilateral vowel space (4 area), irregular pentagonal vowel space (5 area), vowel articulatory index (VAI), formant centralization ratio (FCR) and F2i/F1u ratio (F2 ratio). An experimental group of 32 IPD patients(male:female=16:16) and a control group of twenty healthy people (male:female=8:12) participated in the study and repeated vowels (/a-i-u-e-o/) three times. A correlation analysis was performed among the six parameters, 2-way ANOVA was done with gender and groups as independent factors, and an independent sample t-test was conducted between the male and the female group as post hoc comparison. All parameters were highly correlated with each other and only the FCR showed a high negative correlation with the others. The results of ANOVA showed a significant difference in F2 ratio, 3 area, 4 area and 5 area between gender and in 4 area and 5 area between groups. For the male members of the two groups, significant statistical differences were found in all parameters whereas no such differences were found for the female members. These findings indicated that the vowel space of the female group was wider than the vowel space of the male group. These differences may have been caused by gender-specific speech styles rather than by patho-physiological mechanisms. We also claim that the pentagonal vowel space is better than the other vowel spaces at representing the disordered speech in natural speech situations.

• Journal of Biomedical Engineering Research
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• v.16 no.3
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• pp.345-352
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• 1995

The LPC cepstrum coefficients, which are an acoustic features of speech signal, have been widely used as the feature parameter for various speech recognition systems and showed good performance. The vocal tract area function is a kind of articulatory feature, which is related with the physiological mechanism of speech production. This paper proposes the vocal tract area function as an alternative feature parameter for speech recognition. The linear predictive analysis using Burg algorithm and the vector quantization are performed. Then, recognition experiments for 5 Korean vowels and 10 digits are executed using the conventional LPC cepstrum coefficients and the vocal tract area function. The recognitions using the area function showed the slightly better results than those using the conventional LPC cepstrum coefficients.

• The Journal of the Acoustical Society of Korea
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• v.20 no.6
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• pp.51-56
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• 2001

Recent researches have been focusing on jointly using lip motions and speech for reliable speech recognitions in noisy environments. To this end, this paper proposes the method of combining the visual speech recognizer and the conventional speech recognizer with each output properly weighted. In particular, we propose the method of autonomously determining the weights, depending on the amounts of noise in the speech. The correlations between adjacent speech samples and the residual errors of the LPC analysis are used for this determination. Simulation results show that the speech recognizer combined in this way provides the recognition performance of 83 ％ even in severely noisy environments.