Towards Speaking Style Transplantation in Speech Synthesis

J. Lorenzo-Trueba, R. Barra-Chicote, J. Yamagishi, Oliver Watts, J. M. Montero

Research output: Chapter in Book/Report/Conference proceedingConference contribution


One of the biggest challenges in speech synthesis is the production of naturally sounding synthetic voices. This means that the resulting voice must be not only of high enough quality but also that it must be able to capture the natural expressiveness imbued in human speech. This paper focus on solving the expressiveness problem by proposing a set of different techniques that could be used for extrapolating the expressiveness of proven high quality speaking style models into neutral speakers in HMM-based synthesis. As an additional advantage, the proposed techniques are based on adaptation approaches, which means that they can be used with little training data (around 15 minutes of training data are used in each style for this pa- per). For the final implementation, a set of 4 speaking styles were considered: news broadcasts, live sports commentary, interviews and parliamentary speech. Finally, the implementation of the 5 techniques were tested through a perceptual evaluation that proves that the deviations between neutral and speaking style average models can be learned and used to imbue expressiveness into target neutral speakers as intended.
Original languageEnglish
Title of host publication8th ISCA Workshop on Speech Synthesis - Barcelona, Spain
Number of pages5
Publication statusPublished - Aug 2013


  • Adaptation
  • expressive speech synthesis
  • speaking styles
  • transplantation


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