Part of
In Search of Basic Units of Spoken Language: A corpus-driven approach
Edited by Shlomo Izre'el, Heliana Mello, Alessandro Panunzi and Tommaso Raso
[Studies in Corpus Linguistics 94] 2020
► pp. 285300
References
Avanzi, M., Lacheret, A., & Victorri, B.
(2008) Analor, un outil d’aide pour la modélisation de l’interface prosodie-grammaire. Travaux Linguistiques du CerLiCO, 21, 27–46.Google Scholar
Barbosa, P. A.
(1994) Caractérisation et génération automatique de la structuration rythmique du français (Unpublished doctoral dissertation). Institut National Polytechnique de Grenoble, France).Google Scholar
(1996) At least two macrorhythmic units are necessary for modeling Brazilian Portuguese duration: Emphasis on segmental duration generation. Cadernos de Estudos Linguísticos, 31, 33–53.Google Scholar
(2006) Incursões em torno do ritmo da fala. Campinas: Pontes.Google Scholar
(2007) From syntax to acoustic duration: A dynamical model of speech rhythm production. Speech Communication, 49, 725–742. DOI logoGoogle Scholar
(2010) Automatic duration-related salience detection in Brazilian Portuguese read and spontaneous speech. Proceedings of the Speech Prosody 2010 Conference 10–14 May, Chicago, IL.Google Scholar
Boersma, P. & Weenink, D.
(2017) Praat: Doing phonetics by computer (Version 6.0.29) [Computer software]. Retrieved from [URL]
Botinis, A., Granström, B., & Möbius, B.
(2001) Developments and paradigms in intonation research. Speech Communication, 33, 263–296. DOI logoGoogle Scholar
Campbell, N.
(1993) Automatic detection of prosodic boundaries in speech. Speech Communication, 13(3–4), 343–354. DOI logoGoogle Scholar
Chistovich, L. A., & Ogorodnikova, E. A.
(1982) Temporal processing of spectral data in vowel perception. Speech Communication, 1, 45–54. DOI logoGoogle Scholar
Cresti, E.
(2000) Corpus di italiano parlato (Vol. 1). Florence: Accademia della Crusca.Google Scholar
Cummins, F., & Port, R.
(1998) Rhythmic constraints on stress timing in English. J. Phon, 26, 145–171. DOI logoGoogle Scholar
Eriksson, A., & Heldner, M.
(2015) The acoustics of word stress in English as a function of stress level and speaking style. Proc. of the 16th Annual Conference of the International Speech Communication Association (INTERSPEECH 2015), Dresden, Germany, 41–45.Google Scholar
Godfrey, J. J., Holliman, E. C., & McDaniel, J.
(1992) SWITCHBOARD: Telephone speech corpus for research and development. Proc. of the IEEE International Conference on Acoustics, Speech, and Signal Processing, 1, 517–520.Google Scholar
Gotoy, Y., & Renals, S.
(2000) Sentence boundary detection in broadcast speech transcripts. Proc. of the International Speech Communication Association (ISCA) Workshop: Automatic Speech Recognition: Challenges for the New Millennium (ASR-2000), Paris.Google Scholar
Kim, J.
(2004) Automatic detection of sentence boundaries, disfluencies, and conversational fillers in spontaneous speech (Unpublished doctoral dissertation). University of Washington. Retrieved from [URL]
Lacheret-Dujour, A., Simon, A., Goldman, J., & Avanzi, M.
(2013) Prominence perception and accent detection in French: From phonetic processing to grammatical analysis. Language Sciences, 39, 95–106. DOI logoGoogle Scholar
Mettouchi, A., Lacheret-Dujour, A., Silber-Varod, V., & Izre’el, S.
(2007) Only prosody? Perception of speech segmentation in Kabyle and Hebrew. Nouveaux Cahiers de Linguistique Française, 28, 207–218.Google Scholar
Mittman, M. M., & Barbosa, P. A.
(2016) An automatic speech segmentation tool based on multiple acoustic parameters. CHIMERA. Romance Corpora and Linguistic Studies, 3(2), 133–147.Google Scholar
Ni, C. J., Zhang, A. Y., Liu, W. J., & Xu, B.
(2012) Automatic prosodic break detection and feature analysis. J. Comput. Sci. Technol., 27, 1184–1196. DOI logoGoogle Scholar
Raso, T., Barbosa, P. A., Cavalcante, F. A., & Mittmann, M. M.
this volume). Segmentation and analysis of the two English excerpts: The Brazilian team proposal. In S. Izre’el, H. Mello, A. Panunzi, & T. Raso Eds. In search of basic units of spoken language: A corpus-driven approach Amsterdam John Benjamins
Shriberg, E., Stolcke, A., Hakkani-Tür, D., & Tür, G.
(2000) Prosody-based automatic segmentation of speech into sentences and topics. Speech Communication, 32(1), 127–154. DOI logoGoogle Scholar
Tamburini, F., & Wagner, P.
(2007) On automatic prominence detection for German. Proc. of the 8th Annual Conference of the International Speech Communication Association (INTERSPEECH 2007), (pp. 1809–1812). Antwerp, Belgium.Google Scholar
Teixeira, B., Barbosa, P., & Raso, T.
(2018) Automatic detection of prosodic boundaries in Brazilian Portuguese spontaneous speech. In A. Villavicencio, M. Viviane, A. Abad, H. Caseli, P. Gamallo, C. Ramisch, H. R. Gonçalo Oliveira & G. H. Paetzold (Eds.), Computational processing of the Portuguese language. PROPOR 2018 (pp. 429–437). Canela, Brazil. Cham: Springer. DOI logoGoogle Scholar
Wightman, C. W., Shattuck-Hufnagel, S., Ostendorf, M., & Price, P.
(1992) Segmental durations in the vicinity of prosodic phrase boundaries. J. Acoust. Soc. Am., 91, 1707–1717. DOI logoGoogle Scholar
audio

bp_np_nr

bp_np_re

bp_ra_nr

bp_ra_re

ep_am_nr

ep_am_re

ep_ar_nr

ep_ar_re

fr_ca_nr

fr_ca_re

fr_ma_nr

fr_ma_re

ge_s5_nr

ge_s5_re

ge_s6_nr

ge_s6_re

Cited by

Cited by 1 other publications

Izre'el, Shlomo, Heliana Mello, Alessandro Panunzi & Tommaso Raso
2020. Introduction. In search of a basic unit of spoken language. In In Search of Basic Units of Spoken Language [Studies in Corpus Linguistics, 94],  pp. 1 ff. DOI logo

This list is based on CrossRef data as of 20 march 2024. Please note that it may not be complete. Sources presented here have been supplied by the respective publishers. Any errors therein should be reported to them.