This study focuses on prosodic differences between speaking styles, and their automatic distinction. We aim at characterizing speaking styles with the purpose of distinguishing them from each other, modeling them and eventually adding expressivity to text-to-speech systems. This can be done with a multi-level annotation of varied corpora, based on automatic processes (like phonetic segmentation, grammatical tagging) and manual annotations (of perceived syllabic prominences and of delivery speech objects). Quantitative comparisons of various prosodic parameters are conducted through the acoustic and linguistic dimension to catch differences between speaking genre
International audienceIn the area of large French speech corpora, there is a demonstrated need for a...
In this paper we exhibit macrosyntactic and prosodic fea- tures that are characteristic not only of ...
This paper presents a work-in-progress on the automatic analysis of discourse genre in non-elicited ...
This paper presents the results of a prosodic and phonostylistic analysis based on C-PhonoGenre, an ...
This communication presents partial results from an on-going study on prosodic and phonostylistic va...
This thesis focuses on acoustic and prosodic (fundamental frequency (F0), duration, intensity) analy...
This paper concerns the study of information derived from the melodic, temporal and intensity charac...
International audienceThis paper addresses the problem of modelling prosody for language identificat...
International audienceAfter a brief overview of the phonological and physical parameters of prosody ...
We explore the use of machine learning techniques (notably SVM classifiers and Conditional Random Fi...
Speech can be divided into discourse genres based on the contextual environment it occurs in (e.g. p...
We present the results of a series of experiments in which naive listeners and expert annotators wer...
This paper summarizes a predictive approach to the analysis of prosody in spoken discourse. The actu...
International audienceThe paper presents a software for prosodic and phonostylistic description and ...
International audienceOur study focuses on the issue of prosodic annotation and of the prosody ~ syn...
International audienceIn the area of large French speech corpora, there is a demonstrated need for a...
In this paper we exhibit macrosyntactic and prosodic fea- tures that are characteristic not only of ...
This paper presents a work-in-progress on the automatic analysis of discourse genre in non-elicited ...
This paper presents the results of a prosodic and phonostylistic analysis based on C-PhonoGenre, an ...
This communication presents partial results from an on-going study on prosodic and phonostylistic va...
This thesis focuses on acoustic and prosodic (fundamental frequency (F0), duration, intensity) analy...
This paper concerns the study of information derived from the melodic, temporal and intensity charac...
International audienceThis paper addresses the problem of modelling prosody for language identificat...
International audienceAfter a brief overview of the phonological and physical parameters of prosody ...
We explore the use of machine learning techniques (notably SVM classifiers and Conditional Random Fi...
Speech can be divided into discourse genres based on the contextual environment it occurs in (e.g. p...
We present the results of a series of experiments in which naive listeners and expert annotators wer...
This paper summarizes a predictive approach to the analysis of prosody in spoken discourse. The actu...
International audienceThe paper presents a software for prosodic and phonostylistic description and ...
International audienceOur study focuses on the issue of prosodic annotation and of the prosody ~ syn...
International audienceIn the area of large French speech corpora, there is a demonstrated need for a...
In this paper we exhibit macrosyntactic and prosodic fea- tures that are characteristic not only of ...
This paper presents a work-in-progress on the automatic analysis of discourse genre in non-elicited ...