• Speech Sciences
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• v.9 no.4
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• pp.201-214
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• 2002

In the Japanese language, there is a phonological contrast between not only initial stops, but also non initial in voiced and voiceless sounds. But in the Korean language, voiced sounds do not appear in the initial. Due to this, pronunciation of voiced sounds in the initial will be difficult for Korean. Through this research, I analyzed the minimal pairs by voiced/voiceless sounds of Japanese and Korean, and perception experiment in which Japanese listened to Korean speakers' pronunciations. Japanese pronunciations showed distinct acoustic differences between voiced and voiceless stops, especially in VOT. The duration of vowels after voiced stops was longer than that of voiceless ones. Vowel pitches after voiceless stops were higher. On the other hands, Korean showed three patterns of voiced sounds. There were-VOT values as native speakers, +VOT, and nasal formant tended to occur before prenasalized stops. Koreans pronounced voiceless sounds in strong aspirated, unaspirated, or tense sounds. Finally, Japanese judged sounds with not only -VOT values and prenasalized, but also with +VOT values as voiced. This suggests that we may not consider VOT values as the unique feature of voicing, and that such other phonetic characteristics as the following vowel lengthening should be included here.

• Speech Sciences
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• v.10 no.2
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• pp.207-221
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• 2003

Phonetic voicing does not support the phonological distinction of voiced/voiceless in English stops. The present study is aimed at defining the nature of voicing of English voiced stops. A review of the literature reveals that the voicing is position-conditioned and its length is notably inconsistent relative to the closure duration. No consistent relationships are found between vocal fold adduction and glottal pulsing in initial position. Stress reduced the voicing, etc. The hypothesis for experiments was: (1) active voicing: stress generates longer (stronger) voicing during the closure duration of a voiced stop; (2) passive voicing: stress induces shorter (weaker) voicing during the closure. Instead the voiced stop becomes more voiced when the preceding vowel (syllable) is stressed. The literature review and the results of two experiments comparing English and Slovakian suggested that the voicing of English voiced stops is passive (i.e., a coarticulation of glottal pulsing for adjacent vowels-syllables) and should be distinguished from active voicing in some other languages.

• Speech Sciences
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• v.9 no.3
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• pp.35-45
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• 2002

A simple algorithm for discriminating voiced sounds in a speech is proposed. In addition to low-frequency energy and zero-crossing rate (ZCR), both of which have been widely used in the past for identifying voiced sounds, the proposed algorithm incorporates pitch variation to improve the discrimination rate. Based on TIMIT corpus, evaluation result shows an improvement of 13% in the discrimination of voiced phonemes over that of the traditional algorithm using only energy and ZCR.

• Speech Sciences
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• v.10 no.2
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• pp.7-25
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• 2003

Predicting the right prosodic elements is a key factor in improving the quality of synthesized speech. Prosodic elements include break, pitch, duration and loudness. Pitch, which is realized by Fundamental Frequency (F0), is the most important element relating to the quality of the synthesized speech. However, the previous method for predicting the F0 appears to reveal some problems. If voiced and unvoiced sounds are not correctly classified, it results in wrong prediction of pitch, wrong unit of triphone in synthesizing the voiced and unvoiced sounds, and the sound of click or vibration. This kind of feature is usual in the case of the transformation from the voiced sound to the unvoiced sound or from the unvoiced sound to the voiced sound. Such problem is not resolved by the method of grammar, and it much influences the synthesized sound. Therefore, to steadily acquire the correct value of pitch, in this paper we propose a new model for predicting and classifying the voiced and unvoiced sounds using the CART tool.

• Proceedings of the IEEK Conference
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• 1999.06a
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• pp.1107-1110
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• 1999

In speech signal processing, the accurate decision of the voiced/unvoiced sound is important for robust word recognition and analysis and a high coding efficiency. In this paper, we propose the mehod of the voiced/unvoiced decision using the LSP parameter which represents the spectrum characteristics of the speech signal. The voiced sound has many more LSP parameters in low frequency region. To the contrary, the unvoiced sound has many more LSP parameters in high frequency region. That is, the LSP parameter distribution of the voiced sound is different to that of the unvoiced sound. Also, the voiced sound has the minimun value of sequantial intervals of the LSP parameters in low frequency region. The unvoiced sound has it in high frequency region. we decide the voiced/unvoiced sound by using this charateristics. We used the proposed method to some continuous speech and then achieved good performance.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.32B no.5
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• pp.788-797
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• 1995

In this paper, a variable time-scale modification using SOLA(Synchronized OverLap and Add) is proposed, which takes into consideration the different time-scaled characteristics of voiced and unvoiced speech, Generally, voiced speech is subject to higher variations in length during time-scale modification than unvoiced speech, but the conventional method performs time-scale modification at a uniform rate for all speech. For this purpose, voiced and unvoiced speech duration at various talking speeds were statistically analyzed. The sentences were then spoken at rates of 0.7, 1.3, 1.5 and 1.8 times normal speed. A clipping autocorrelation function was applied to each analysis frame to determine voiced and unvoiced speech to obtain respective variation rates. The results were used to perform variable time-scale modification to produce sentences at rates of 0.7, 1.3, 1.5, 1.8 times normal speed. To evaluate performance, a MOS test was conducted to compare the proposed voiced/unvoiced variable time-scale modification and the uniform SOLA method. Results indicate that the proposed method produces sentence quality superior to that of the conventional method.

• Korean Journal of English Language and Linguistics
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• v.2 no.1
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• pp.23-30
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• 2002

Phonologically, the difference between the English stops /b, d, g/ and /p, t, k/ is carried by the presence or the absence of the vocal fold vibration throughout their oral closure phase. If phonology has its foundation in phonetics, there must be phonetic evidence for the voiced-voiceless distinction. This study is aimed to determine whether or not the voiced-voiceless distinction is acceptable or proper in English. The determination was based mainly on findings in the existing literature and in informal experiments. In conclusion, there is no phonetic evidence for the voiced-voiceless distinction both in production and perception. The [voice] appears to be one of potential phonetic correlates of the phonologically voiced stop. It is improper to use the [voice] as independent phonological marker, regardless of position (word-initial, intervocalic, word-final). A feature other than the voiced-voiceless feature must distinguish /b, d, g/ from /p, t, k/.

• Speech Sciences
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• v.4 no.2
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• pp.41-54
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• 1998

Speech signals are, depending on the characteristics of waveform, classified as voiced sound, unvoiced sound, and silence. Voiced sound, produced by an air flow generated by the vibration of the vocal cords, is quasi-periodic, while unvoiced sound, produced by a turbulent air flow passed through some constriction in the vocal tract, is noise-like. Silence represents the ambient noise signal during the absence of speech. The need for deciding whether a given segment of a speech waveform should be classified as voiced, unvoiced, or silence has arisen in many speech analysis systems. In this paper, a voiced/unvoiced/silence classification algorithm using spectral change in the wavelet transformed signal is proposed and then, experimental results are demonstrated with our discussions.

• Proceedings of the IEEK Conference
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• 2001.06d
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• pp.281-284
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• 2001

Speech is classified into voiced signal and unvoiced signal. Since the amplitude of voiced fall off at about -20dB/decade, dynamic range is often compressed prior to spectral analysis so that details at weak, high frequencies may be visible[5][6] There is a distinct difference in spectrum slope between voiced signal and unvoiced signal. In this paper, we got the slope of each frame by using autocorrelation method, and determined voiced /unvoiced region. Also, we used energy to decide region of silence. To show experimental results, we allot to 1 value in voiced region, -1 value in unvoiced region and 0 value in silence region.

• Proceedings of the Acoustical Society of Korea Conference
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• 1994.06c
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• pp.111-115
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• 1994

In this paper, a variable time-scale modification using SOLA is proposed, which takes into consideration the different time-scaled characteristics of voiced and unvoiced speech. The conventional method performs time-scale modifiction at a uniform rate for all speech. For this purpose, voiced and unvoiced speech duration at various taling speeds were statistically analyzed. A clipping autocorrelation functio was applied to each analysis frame to detemine voiced and unvoiced speech to obtain respective variation rates. The results were used to perform variable time-scale modification to evaluate performance, a MOS test was conducted to compare the proposed voiced/unvoiced variable time-scale modification and the uniform SOLA method. Results indicate that the proposed method produces sentence quality superior to that of the conventional method.