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Using the unit selection technique [7], we can select and join audiovisual segments from an audiovisual speech database, such that the final output signal will consist of concatenated original combinations of auditory and visual speech.
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The weight set corresponding to the point on the Pareto-front with maximal similarity are used in the unit selection.
Each suffix type was required to contain at least 15 instances in the database before it could be used in the unit selection database.
FIDM is used to evaluate the unit selection and the Pareto optimization accelerates the training process.
The unit selection is refined in this paper, and Pareto optimization is used to train the unit selection.
Table 1 Details of the audiobook used for building the unit selection voice Name of the audiobook Author Read by Running time Olive (voice 1) Dinah Maria Mulock CRAIK Arielle Lipshaw 14 03:13 Table 2 Details of the lecture speech used for building the unit selection voice Name of the course Instructor Running time Introduction to Public Speaking (voice 2) Dr. Matt McGarrity ≈12 h.
The unit selection selects the mouth images corresponding to the phoneme sequence, using a target cost and a concatenation cost function to balance lip synchronization and smoothness.
More recent systems use techniques similar to the unit selection strategy found in audio TTS systems.
Commonly occurring suffixes in Turkish are stored in the unit selection database and used in the proposed system.
We adopted the unit selection method to work with multimodal units, using audiovisual selection costs.
An approach similar to weight space search is presented in [11], which uses only one objective measurement to train the weights of the unit selection.
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