@inproceedings{56c6b831bd3241179bcd4b62da7e7e47,
title = "Mixing HMM-based spanish speech synthesis with a CBR for prosody estimation",
abstract = "Hidden Markov Models based text-to-speech (HMM-TTS) synthesis is a technique for generating speech from trained statistical models where spectrum, pitch and durations of basic speech units are modelled altogether. The aim of this work is to describe a Spanish HMMTTS system using an external machine learning technique to help improving the expressiveness. System performance is analysed objectively and subjectively. The experiments were conducted on a reliably labelled speech corpus, whose units were clustered using contextual factors based on the Spanish language. The results show that the CBR-based F0 estimation is capable of improving the HMM-based baseline performance when synthesizing non-declarative short sentences while the durations accuracy is similar with the CBR. or the HMM system.",
author = "Xavi Gonzalvo and Ignasi Iriondo and Socor{\'o}, \{Joan Claudi\} and Francesc Alias and Carlos Monzo",
year = "2007",
doi = "10.1007/978-3-540-77347-4\_4",
language = "English",
isbn = "3540773460",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "78--85",
booktitle = "Advances in Nonlinear Speech Processing - International Conference on Nonlinear Speech Processing, NOLISP 2007, Revised Selected Papers",
address = "Germany",
note = "International Conference on Nonlinear Speech Processing, NOLISP 2007 ; Conference date: 22-05-2007 Through 25-05-2007",
}