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ICA-based hierarchical text classification for multi-domain text-to-speech synthesis

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3 Author(s)
Sevillano, X. ; Department of Communications and Signal Theory. Enginyeria i Arquitectura La Salle. Universitat Ramon Llull. Barcelona, Spain ; Alias, F. ; Socoro, J.C.

In the framework of multi-domain text-to-speech synthesis, it is essential (i) to design a hierarchically structured database for allowing several domains in the same speech corpus and (ii) to include a text classification module that, at run time, assigns the input sentences to a domain or set of domains from the database. We present a hierarchical text classifier based on independent component analysis (ICA), which is capable of (i) organizing the contents of the corpus in a hierarchical manner and (ii) classifying the texts to be synthesized according to the learned structure. The document organization and classification performance of our ICA-based hierarchical classifier are evaluated in several encouraging experiments conducted on a journalistic-style text corpus for speech synthesis in Catalan.

Published in:

Acoustics, Speech, and Signal Processing, 2004. Proceedings. (ICASSP '04). IEEE International Conference on  (Volume:5 )

Date of Conference:

17-21 May 2004