• Title/Summary/Keyword: vowel identity

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Phonation Type Index k (발성유형지수 k)

  • Park Hansang
    • Proceedings of the KSPS conference
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    • 2002.11a
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    • pp.77-80
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    • 2002
  • This study proposes phonation type index k as a descriptor of the overall spectral tilt, which is free from the effects of fundamental frequency and vowel quality. The newly proposed phonation type index k presents a simple and single measure of the overall spectral tilt. Phonation type index k can be applied to speech technology. It can also be used in diagnosing patients voice qualities in speech pathology. The distribution of phonation type index k, which is speaker-dependent, may be useful in forensic phonetics and voice recognition as an indicator of speaker identity.

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Shapes of Vowel F0 Contours Influenced by Preceding Obstruents of Different Types - Automatic Analyses Using Tilt Parameters-

  • Jang, Tae-Yeoub
    • Speech Sciences
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    • v.11 no.1
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    • pp.105-116
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    • 2004
  • The fundamental frequency of a vowel is known to be affected by the identity of the preceding consonant. The general agreement is that strong consonants trigger higher F0 than weak consonants. However, there has been a disagreement on the shape of this segmentally affected F0 contours. Some studies report that shapes of contours are differentiated based on the consonant type, but others regard this observation as misleading. This research attempts to resolve this controversy by investigating shapes and slopes of F0 contours of Korean word level speech data produced by four male speakers. Instead of entirely relying on traditional human intuition and judgment, I employed an automatic F0 contour analysis technique known as tilt parameterisation (Taylor 2000). After necessary manipulation of an F0 contour of each data token, various parameters are collapsed into a single tilt value which directly indicates the shape of the contour. The result, in terms of statistical inference, shows that it is not viable to conclude that the type of consonant is significantly related to the shape of F0 contour. A supplementary measurement is also made to see if the slope of each contour bears meaningful information. Unlike shapes themselves, slopes are suspected to be practically more practical for consonantal differentiation, although confirmation is required through further refined experiments.

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Input- Truncatum Faithfulness in English Hypocoristic Names

  • Hwangbo, Young-Shik
    • Korean Journal of English Language and Linguistics
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    • v.2 no.2
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    • pp.287-304
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    • 2002
  • Truncated forms (truncata) in English hypocoristic words have been argued to be faithful to their bases. This means that “ ... the base of truncation is an output form"”(Benua 1995:6,12). For example, in some non-rhotic dialects where syllable-final [r]s are deleted, the [r]s of truncated names such as Gar [gær] (truncated form of Garry [gæri]) are not deleted although they are syllable-final. This is an example of base-truncatum identity. That is, the syllable-final [r] is retained to make the truncatum more faithful to its base. However, there are many English hypocoristic names which are not faithful to their base forms. For example, Letty [equation omitted] (hypocoristic form of Latitia [equation omitted]) is not faithful to its base; the first vowel and the second consonant of the truncatum are not identical to the corresponding segments of the base. It will be argued, therefore, that some truncated forms are more faithful to the inputs than the bases. It will also be argued that McCarthy and Prince's (1995) Full Model is needed to deal successfully with all the phenomena related to truncation.

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Effects of phonological and phonetic information of vowels on perception of prosodic prominence in English

  • Suyeon Im
    • Phonetics and Speech Sciences
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    • v.15 no.3
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    • pp.1-7
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    • 2023
  • This study investigates how the phonological and phonetic information of vowels influences prosodic prominence among linguistically untrained listeners using public speech in American English. We first examined the speech material's phonetic realization of vowels (i.e., maximum F0, F0 range, phone rate [as a measure of duration considering the speech rate of the utterance], and mean intensity). Results showed that the high vowels /i/ and /u/ likely had the highest max F0, while the low vowels /æ/ and /ɑ/ tended to have the highest mean intensity. Both high and low vowels had similarly high phone rates. Next, we examined the effects of the vowels' phonological and phonetic information on listeners' perceptions of prosodic prominence. The results showed that vowels significantly affected the likelihood of perceived prominence independent of acoustic cues. The high and low vowels affected probability of perceived prominence less than the mid vowels /ɛ/ and /ʌ/, although the former two were more likely to be phonetically enhanced in the speech than the latter. Overall, these results suggest that perceptions of prosodic prominence in English are not directly influenced by signal-driven factors (i.e., vowels' acoustic information) but are mediated by expectation-driven factors (e.g., vowels' phonological information).

Study on the Neural Network for Handwritten Hangul Syllabic Character Recognition (수정된 Neocognitron을 사용한 필기체 한글인식)

  • 김은진;백종현
    • Korean Journal of Cognitive Science
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    • v.3 no.1
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    • pp.61-78
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    • 1991
  • This paper descibes the study of application of a modified Neocognitron model with backward path for the recognition of Hangul(Korean) syllabic characters. In this original report, Fukushima demonstrated that Neocognitron can recognize hand written numerical characters of $19{\times}19$ size. This version accepts $61{\times}61$ images of handwritten Hangul syllabic characters or a part thereof with a mouse or with a scanner. It consists of an input layer and 3 pairs of Uc layers. The last Uc layer of this version, recognition layer, consists of 24 planes of $5{\times}5$ cells which tell us the identity of a grapheme receiving attention at one time and its relative position in the input layer respectively. It has been trained 10 simple vowel graphemes and 14 simple consonant graphemes and their spatial features. Some patterns which are not easily trained have been trained more extrensively. The trained nerwork which can classify indivisual graphemes with possible deformation, noise, size variance, transformation or retation wre then used to recongnize Korean syllabic characters using its selective attention mechanism for image segmentation task within a syllabic characters. On initial sample tests on input characters our model could recognize correctly up to 79%of the various test patterns of handwritten Korean syllabic charactes. The results of this study indeed show Neocognitron as a powerful model to reconginze deformed handwritten charavters with big size characters set via segmenting its input images as recognizable parts. The same approach may be applied to the recogition of chinese characters, which are much complex both in its structures and its graphemes. But processing time appears to be the bottleneck before it can be implemented. Special hardware such as neural chip appear to be an essestial prerquisite for the practical use of the model. Further work is required before enabling the model to recognize Korean syllabic characters consisting of complex vowels and complex consonants. Correct recognition of the neighboring area between two simple graphemes would become more critical for this task.