7th International Conference on Spoken Language Processing
September 16-20, 2002
In our recent work on concatenative speech synthesis, we have devised an efficient, graph-based search to perform unit selection given symbolic information. By encapsulating concatenation and substitution costs defined at the class level, the graph expands only linearly with respect to corpus size. To date, these costs were manually tuned over pre-specified classes, which was a knowledge-intensive engineering process. In this research paper, we turn to informationtheoretic metrics for automatically learning the costs from data. These costs can be analyzed in a minimum description length (MDL) framework. The performance of these automatically determined weights is compared against that of manually tuned weights in a perceptual evaluation.
Bibliographic reference. Yi, Jon / Glass, James (2002): "Information-theoretic criteria for unit selection synthesis", In ICSLP-2002, 2617-2620.