TY - CHAP A1 - Pouget, Maël A1 - Hueber, Thomas A1 - Bailly, Gérard A1 - Baumann, Timo T1 - HMM training strategy for incremental speech synthesis T2 - Interspeech 2015, Dresden, Germany, 6-10 September 2015 N2 - Incremental speech synthesis aims at delivering the synthetic voice while the sentence is still being typed. One of the main challenges is the online estimation of the target prosody from a partial knowledge of the sentence's syntactic structure. In the context of HMM-based speech synthesis, this typically results in missing segmental and suprasegmental features, which describe the linguistic context of each phoneme. This study describes a voice training procedure which integrates explicitly a potential uncertainty on some contextual features. The proposed technique is compared to a baseline approach (previously published), which consists in substituting a missing contextual feature by a default value calculated on the training set. Both techniques were implemented in a HMM-based Text-To-Speech system for French, and compared using objective and perceptual measurements. Experimental results show that the proposed strategy outperforms the baseline technique for this language. KW - HMM-based speech synthesis KW - incremental KW - TTS KW - HTS KW - prosody Y1 - 2015 U6 - https://doi.org/10.21437/Interspeech.2015-304 SP - 1201 EP - 1205 PB - ISCA ER -