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Voice modulation, self-perception and motor branch of the superior laryngeal nerve ; Modulation vocale, ressenti et branche motrice du nerf laryngé supérieur
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In: ISSN: 1879-7296 ; EISSN: 1879-730X ; European Annals of Otorhinolaryngology, Head and Neck Diseases ; https://hal.archives-ouvertes.fr/hal-03504625 ; European Annals of Otorhinolaryngology, Head and Neck Diseases, Elsevier Masson, 2021, 138 (4), pp.241-245. ⟨10.1016/j.anorl.2020.11.007⟩ (2021)
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Emoción, percepción, producción: un estudio psicolingüístico para detectar emociones en el habla
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Pitch as the Main Determiner of Italian Lexical Stress Perception Across the Lifespan : Evidence From Typical Development and Dyslexia
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СОПОСТАВЛЕНИЕ АКУСТИЧЕСКОЙ ПРИРОДЫ СЛОВЕСНОГО УДАРЕНИЯ В СЕРБСКОМ И РУССКОМ ЯЗЫКАХ
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Панова, Екатерина. - : Федеральное государственное бюджетное образовательное учреждение высшего профессионального образования "Государственная академия славянской культуры", 2015
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Variabilidad intra- e inter-hablante de la fricativa sibilante /s/ en el español de Argentina ; Intra- and inter-speaker variability of sibilant fricative /s/ in Argentine Spanish
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In: Estudios de fonética experimental; 2014: Vol.: 23; p. 95-124 (2015)
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Acoustic correlates of masculinity in voices of Lebanese women with Reinke's edema
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In: International Seminar on Speech Production (ISSP) 10 ; https://hal.archives-ouvertes.fr/hal-01507720 ; International Seminar on Speech Production (ISSP) 10, May 2014, Cologne, Germany. pp.273-276 (2014)
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Analogy between Laryngeal Gesture in Mongolian Long Song and Supracricoid Partial Laryngectomy
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In: ISSN: 0269-9206 ; EISSN: 1464-5076 ; Clinical Linguistics & Phonetics ; https://halshs.archives-ouvertes.fr/halshs-00675031 ; Clinical Linguistics & Phonetics, Taylor & Francis, 2012, 26 (1), pp.86-99. ⟨10.3109/02699206.2011.590920⟩ (2012)
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Quantitative microlaryngoscopic measurements of vocal fold polyps, glottal gap and their relation to vocal function
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In: Medicina ; Volume 44 ; Issue 4 (2008)
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Cognitive maturation and the use of pitch and rate information in making similarity judgments of a single talker
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In: JOURNAL OF SPEECH LANGUAGE AND HEARING RESEARCH , 51 (2) 485 - 501. (2008) (2008)
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Analysis, Vocal-tract modeling, and Automatic Detection of Vowel Nasalization
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Abstract:
The aim of this work is to clearly understand the salient features of nasalization and the sources of acoustic variability in nasalized vowels, and to suggest Acoustic Parameters (APs) for the automatic detection of vowel nasalization based on this knowledge. Possible applications in automatic speech recognition, speech enhancement, speaker recognition and clinical assessment of nasal speech quality have made the detection of vowel nasalization an important problem to study. Although several researchers in the past have found a number of acoustical and perceptual correlates of nasality, automatically extractable APs that work well in a speaker-independent manner are yet to be found. In this study, vocal tract area functions for one American English speaker, recorded using Magnetic Resonance Imaging, were used to simulate and analyze the acoustics of vowel nasalization, and to understand the variability due to velar coupling area, asymmetry of nasal passages, and the paranasal sinuses. Based on this understanding and an extensive survey of past literature, several automatically extractable APs were proposed to distinguish between oral and nasalized vowels. Nine APs with the best discrimination capability were selected from this set through Analysis of Variance. The performance of these APs was tested on several databases with different sampling rates, recording conditions and languages. Accuracies of 96.28%, 77.90% and 69.58% were obtained by using these APs on StoryDB, TIMIT and WS96/97 databases, respectively, in a Support Vector Machine classifier framework. To my knowledge, these results are the best anyone has achieved on this task. These APs were also tested in a cross-language task to distinguish between oral and nasalized vowels in Hindi. An overall accuracy of 63.72% was obtained on this task. Further, the accuracy for phonemically nasalized vowels, 73.40%, was found to be much higher than the accuracy of 53.48% for coarticulatorily nasalized vowels. This result suggests not only that the same APs can be used to capture both phonemic and coarticulatory nasalization, but also that the duration of nasalization is much longer when vowels are phonemically nasalized. This language and category independence is very encouraging since it shows that these APs are really capturing relevant information.
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Keyword:
Acoustic parameters; Electronics and Electrical; Engineering; Hindi; Language; Linguistics; Nasal; Phonetic features; Speech Communication; Speech Recognition; Vocal tract modeling
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URL: http://hdl.handle.net/1903/4273
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Calgary Working Papers in Linguistics, Volume 16, Winter 1994 ...
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Parameters for Automatic Speaker Recognition over LPC (Linear Predictive-Coding) Systems.
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In: DTIC AND NTIS (1986)
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www.elsevier.com/locate/specom Acoustic parameters for automatic detection of nasal manner
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In: http://www.isr.umd.edu/Labs/SCL/publications/journal/pruthi_espy_sc_04.pdf
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