Abstract
In the framework of multi-domain Text-to-Speech synthesis it is essential to (i) design a hierarchically structured database for allowing several domains in the same speech corpus and (ii) include a text classification module that, at run time, assigns the input sentences to a domain or set of domains from the database. In this paper, 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.
| Original language | English |
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| Pages (from-to) | V-697-V-700 |
| Journal | ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings |
| Volume | 5 |
| Publication status | Published - 2004 |
| Event | Proceedings - IEEE International Conference on Acoustics, Speech, and Signal Processing - Montreal, Que, Canada Duration: 17 May 2004 → 21 May 2004 |