11th Annual Conference of the International Speech Communication Association

Makuhari, Chiba, Japan
September 26-30. 2010

Using Robust Viterbi Algorithm and HMM-Modeling in Unit Selection TTS to Replace Units of Poor Quality

Hanna Silén (1), Elina Helander (1), Jani Nurminen (2), Konsta Koppinen (1), Moncef Gabbouj (1)

(1) Tampere University of Technology, Finland
(2) Nokia Devices R&D, Finland

In hidden Markov model-based unit selection synthesis, the benefits of both unit selection and statistical parametric speech synthesis are combined. However, conventional Viterbi algorithm is forced to do a selection also when no suitable units are available. This can drift the search and decrease the overall quality. Consequently, we propose to use robust Viterbi algorithm that can simultaneously detect bad units and select the best sequence. The unsuitable units are replaced using hidden Markov model-based synthesis. Evaluations indicate that the use of robust Viterbi algorithm combined with unit replacement increases the quality compared to the traditional algorithm.

Full Paper

Bibliographic reference.  Silén, Hanna / Helander, Elina / Nurminen, Jani / Koppinen, Konsta / Gabbouj, Moncef (2010): "Using robust viterbi algorithm and HMM-modeling in unit selection TTS to replace units of poor quality", In INTERSPEECH-2010, 166-169.