HMM-based prosodic structure model using rich linguistic context

This paper presents a study on the use of deep syntactical features to improve prosody modeling 1 . A French linguistic processing chain based on linguistic preprocessing, morphosyntactical labeling, and deep syntactical parsing is used in order to extract syntactical features from an input text. These features are used to define more or less high-level syntactical feature sets. Such feature sets are compared on the basis of a HMM-based prosodic structure model. High-level syntactical features are shown to significantly improve the performance of the model (up to 21% error reduction combined with 19% BIC reduction).

• Type: Journal
• Year: 2010
• Where: INTERSPEECH
• Authors: Nicolas Obin, Xavier Rodet, Anne Lacheret
• Keywords: Deep Syntactical Features, Deep Syntactical Parsing, INTERSPEECH 2010, Signal Processing, Syntactical Features