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Communication dans un congrès Année : 2008

French Prominence: a Probabilistic Framework

Résumé

Identification of prosodic phenomena is of first importance inprosodic analysis and modeling. In this paper, we introduce anew method for automatic prosodic phenomena labelling. The au-thors set their approach of prosodic phenomena in the frameworkof prominence. The proposed method for automatic prominencelabelling is based on well-known machine learning techniques ina three step procedure: i) a feature extraction step in which wepropose a framework for systematic and multi-level speech acousticfeature extraction, ii) a feature selection step for identifying the morerelevant prominence acoustic correlates, and iii) a modelling step inwhich a gaussian mixture model is used for predicting prominence.This model shows robust performance on read speech (84%).
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Dates et versions

halshs-00334343, version 1 (25-10-2008)

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Nicolas Obin, Xavier Rodet, Anne Lacheret. French Prominence: a Probabilistic Framework. International Conference on Acoustics, Speech, and Signal Processing (ICASSP), Mar 2008, Las Vegas, United States. pp.3993-3996, ⟨10.1109/ICASSP.2008.4518529⟩. ⟨halshs-00334343⟩
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