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The paper has two goals: to present a toolbox for prosodic and phonostylistic description, and to use it for studying a specific radio style. This tool is quasi-automatic and modular. It consists of a set of Praat-based scripts like phonetic segmentation, melodic stylisation and prominence detection. It produces a phonostylistic report – called ProsoReport(More)
The automatic detection of prosodically prominent syllables is crucial for analysing speech, especially in French where prominence contributes substantially to prosodic grouping and boundary demarcation. In this paper, we compare different machine learning techniques for the automatic detection of prominent syllables, using prosodic features (including(More)
The goal of this paper is to shed new light on accentuation in French, more precisely to discuss the role of grammatical constraints and of phonetic factors implicated in the perception of French final and non-final accent. The study is based on the analysis of a 70-minute long corpus, including various speaking styles. The corpus has been annotated(More)
In the area of large speech corpora, there is a definite need for common prosodic notation system based on efficient (semi)-automating tools of prosodic segmentation and labelling. In this context, we present the software program ANALOR, developed in order to process semi-automatically prosodic data. From a text-sound alignment, this computer tool detects(More)
The aim of this paper is to present a software tool called ANALOR, which allows semi-automatic prominence detection in spontaneous French. On the basis of a manual annotation performed by two experts on a 70-minute long corpus including different regional varieties of French (Belgian, Swiss and metropolitan French) and various discourse genres (from read(More)
We present DisMo, a multi-level annotator for spoken language corpora that integrates part-of-speech tagging with basic disfluency detection and annotation, and multi-word unit recognition. DisMo is a hybrid system that uses a combination of lexical resources, rules, and statistical models based on Conditional Random Fields (CRF). In this paper, we present(More)
A major drawback of current Hidden Markov Model (HMM)-based speech synthesis is the monotony of the generated speech which is closely related to the monotony of the generated prosody. Complementary to model-oriented approaches that aim to increase the prosodic variability by reducing the " over-smoothing " effect, this paper presents a linguistic-oriented(More)
Prosodic transcription of spoken corpora relies mainly on the identification of perceived prominence. However, the manual annotation of prominent phenomena is extremely time-consuming, and varies greatly from one expert to another. Automating this procedure would be of great importance. In this study, we present the first results of a methodology aiming at(More)
The aim of this paper is to present a tool developed in order to generate French rhythmical structure semi-automatically, without taking grammatical cues into account. On the basis of a phonemic alignment, the software first locates prominent syllables by considering basic acoustic features such as F0, duration and silent pause. It then assigns a degree of(More)