Aspects relatifs à la transcription phonétique interactive du signal audio.
The paper presents the results obtained in the interactive phonetic transcription for the Romanian vowels [a], [e] and [i]. After a brief introduction, the resource creation process is presented. A subset of video recordings are selected from the site of Atlasul lingvistic audiovizual al Bucovinei (...
| Published in: | Conference Proceedings of the Annual International Symposium Organized by 'A. Philippide' Institute of Romanian Philology pp. 35 - 51 |
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| Main Authors: | , , , |
| Format: | Article |
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Institutul de Filologie Romana A. Philippide
2015
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| Online Access: | View this record in EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=hlh&AN=138134730&site=ehost-live header: @attributes: shortDbName: hlh uiTerm: 138134730 longDbName: Humanities International Complete uiTag: AN controlInfo: bkinfo: jinfo: jid: LF1E jtl: Conference Proceedings of the Annual International Symposium Organized by 'A. Philippide' Institute of Romanian Philology maglogo: N pubinfo: dt: 2015 pid: 50276 pub: Institutul de Filologie Romana A. Philippide artinfo: ui: 138134730 ppf: 35 ppct: 16 formats: tig: atl: Aspects relatifs à la transcription phonétique interactive du signal audio. aug: au: BOTOŞINEANU, LUMINIŢA MUSCĂ, ELENA OLARIU, FLORIN-TEODOR PĂVĂLOI, IOAN affil: Institut de Philologie Roumaine „A. Philippide”, Iaşi, Roumanie. Institut d’Informatique Théorique, Iaşi, Roumanie. sug: keyword: ALR_IIT interactive phonetic transcription k-NN MFCC PLP SVM ALR_IIT interactive phonetic transcription k-NN MFCC PLP SVM ab: The paper presents the results obtained in the interactive phonetic transcription for the Romanian vowels [a], [e] and [i]. After a brief introduction, the resource creation process is presented. A subset of video recordings are selected from the site of Atlasul lingvistic audiovizual al Bucovinei (ALAB) [Audiovisual Linguistic Atlas of Bucovina]. The audio parts, extracted and manually annotated using the Praat software, were phonetically transcribed using the ALR_IIT editor. These result in six sets of feature vectors generated using F0-F3 formant values, MFCC (Mel-Frequency Cepstral Coefficients) coefficients and PLP (Perceptual Linear Prediction) coefficients. For the recognition we used two discriminative classification algorithm: k-NN, for k=1, k=3 and k=5, and SVM. For the k-NN algorithm, we used three distances: Euclidian, Manhattan and Canberra. The results obtained for [a], [e] and [i] are then discussed in detail. The last section is dedicated to the conclusions and to the prospects of our research. pubtype: Conference Proceedings doctype: Article src: R language: French refInfo: copyright: @attributes: flag: Y dt: @attributes: year: 2015 holdings: @attributes: islocal: N |
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