Towards Automatic Classification of Speech Styles

Autor:	Jorge Proença, Dirce Celorico, Sara Candeias, Arlindo Veiga, Fernando Perdigão
Rok vydání:	2012
Předmět:	Audio mining business.industry Computer science Speech recognition Acoustic model Speech corpus computer.software_genre Speech processing Speaking style Speech analytics Audio segmentation Artificial intelligence business computer News media Natural language processing
Zdroj:	Lecture Notes in Computer Science ISBN: 9783642288845 PROPOR
DOI:	10.1007/978-3-642-28885-2_47
Popis:	In this paper we present results from a study seeking to distinguish "unprepared" from "prepared" speech in broadcast news media. The idea is to explore the results from a previous experiment concerning the characterization of filled pauses and extensions, extending the analysis of such hesitation phenomena to large audio corpus. Daily news broadcasts of Portuguese television were segmented and labeled manually in terms of several speech styles, over a range of background environments. An automatic detection of filled pauses and extensions in this audio data allowed us to correlate the presence of hesitation events with segments of unprepared speech. Distinguishing unprepared speech from prepared speech is of considerable practical interest for audio segmentation, speech processing and linguistic research. The long-term objective of this work is to automatically segment all audio genres and speaking styles as well as identify prosodic and linguistic features of the speech segments.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::0c3c0fbef63328261f33cc8f9fdeb53a https://doi.org/10.1007/978-3-642-28885-2_47 Zobrazit plný text záznamu