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1
Predicting synthetic voice style from facial expressions. An application for augmented conversations
In: Speech communication. - Amsterdam [u.a.] : Elsevier 57 (2014), 63-75
OLC Linguistik
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2
Advances in nonlinear speech processing : 6th international conference ; proceedings
Solé-Casals, Jordi; Carson-Berndsen, Julie; Daoudi, Khalid. - Heidelberg [u.a.] : Springer, 2013
BLLDB
UB Frankfurt Linguistik
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3
Evaluating expressive speech synthesis from audiobooks in conversational phrases
BASE
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4
Rapidly Testing the Interaction Model of a Pronunciation Training System via Wizard-of-Oz.
Cabral, Joao P; Kane, Mark; Ahmed, Zeeshan. - : University College Dublin, Ireland, 2012
BASE
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5
WinkTalk: a multimodal speech synthesis interface linking facial expressions to expressive synthetic voices
BASE
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6
WinkTalk : a demonstration of a multimodal speech synthesis platform linking facial expressions to expressive synthetic voices
Székely, Éva; Carson-Berndsen, Julie; Ahmed, Zeeshan. - : Association for Computational Linguistics, 2012
BASE
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7
Clustering Expressive Speech Styles in Audiobooks Using Glottal Source Parameters.
Székely, Éva; Cabral, Joao P; Cahill, Peter. - : ISCA-INT SPEECH COMMUNICATION ASSOC, 2011
BASE
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8
Transforming Voice Source Parameters in a HMM-based Speech Synthesiser with Glottal Post-Filtering
Abstract: Control over voice quality, e.g. breathy and tense voice, is important for speech synthesis applications. For example, transformations can be used to modify aspects of the voice re- lated to speaker's identity and to improve expressiveness. How- ever, it is hard to modify voice characteristics of the synthetic speech, without degrading speech quality. State-of-the-art sta- tistical speech synthesisers, in particular, do not typically al- low control over parameters of the glottal source, which are strongly correlated with voice quality. Consequently, the con- trol of voice characteristics in these systems is limited. In con- trast, the HMM-based speech synthesiser proposed in this paper uses an acoustic glottal source model. The system passes the glottal signal through a whitening filter to obtain the excitation of voiced sounds. This technique, called glottal post-filtering, allows to transform voice characteristics of the synthetic speech by modifying the source model parameters. We evaluated the proposed synthesiser in a perceptual ex- periment, in terms of speech naturalness, intelligibility, and similarity to the original speaker's voice. The results show that it performed as well as a HMM-based synthesiser, which generates the speech signal with a commonly used high-quality speech vocoder.
URL: http://hdl.handle.net/1842/4662
BASE
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9
HMM-based speech synthesis using an acoustic glottal source model
Cabral, Joao P. - : The University of Edinburgh, 2011
BASE
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10
Glottal Source and Prosodic Prominence Modelling in HMM-based Speech Synthesis for the Blizzard Challenge 2009
BASE
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11
Glottal Spectral Separation for Parametric Speech Synthesis
BASE
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12
Towards an improved modeling of the glottal source in statistical parametric speech synthesis
BASE
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