Mathieu Avanzi

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  • M Avanzi, A C Simon, J.-P Goldman, A Auchlin
  • 2010
This paper presents C-PROM, an annotated corpus for French prominence studies. The corpus, including different regional varieties of French (Belgian, Swiss and metropolitan French) and various discourse-genres (from oral reading to spontaneous conversations) for a total duration of 70 minutes, was annotated by two phonetics experts. The two experts in(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)
  • Jean-Philippe Goldman, Antoine Auchlin, Sophie Roekhaut, Anne Catherine Simon, Mathieu Avanzi
  • 2010
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)
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)
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)
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)
In this paper an attempt is made to automatically recognize the speaker's accent among regional Swiss French accents from four different regions of Switzerland, i.e. Geneva (GE), Martigny (MA), Neuchâtel (NE) and Nyon (NY). To achieve this goal, we rely on a generative probabilistic framework for classification based on Gaussian mixture modelling (GMM). Two(More)