Abstract:Data sparsity is a major problem for data driven prosodic models. Being able to share prosodic data across speakers is a potential solution to this problem. This paper explores this potential solution by addressing two questions: 1) Does a larger less sparse model from a different speaker produce more natural speech than a small sparse model built from the original speaker? 2)Does a different speaker's larger model generate more unit selection errors than a small sparse model built from the original speaker?A … Show more
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