Robustness of HMM-based speech synthesis, Proc. of Interspeech, pp.2-5, 2008. ,
Statistical parametric speech synthesis using deep neural networks, 2013 IEEE International Conference on Acoustics, Speech and Signal Processing, pp.7962-7966, 2013. ,
DOI : 10.1109/ICASSP.2013.6639215
Speech synthesis by rule using an optimal selection of non-uniform synthesis units, ICASSP-88., International Conference on Acoustics, Speech, and Signal Processing, pp.679-682, 1988. ,
DOI : 10.1109/ICASSP.1988.196677
CHATR, Proceedings of the 15th conference on Computational linguistics -, pp.983-986, 1994. ,
DOI : 10.3115/991250.991307
Unit selection in a concatenative speech synthesis system using a large speech database, 1996 IEEE International Conference on Acoustics, Speech, and Signal Processing Conference Proceedings, pp.373-376, 1996. ,
DOI : 10.1109/ICASSP.1996.541110
The architecture of the Festival speech synthesis system, Proc. of the ESCA Workshop in Speech Synthesis, pp.147-151, 1998. ,
Non-uniform unit selection and the similarity metric within BTs Laureate TTS system, Proc. of the ESCA Workshop on Speech Synthesis, pp.373-376, 1998. ,
Multisyn: Open-domain unit selection for the Festival speech synthesis system, Speech Communication, vol.49, issue.4, pp.317-330, 2007. ,
DOI : 10.1016/j.specom.2007.01.014
URL : https://hal.archives-ouvertes.fr/hal-00499177
A syllable-based framework for unit selection synthesis in 13 Indian languages, 2013 International Conference Oriental COCOSDA held jointly with 2013 Conference on Asian Spoken Language Research and Evaluation (O-COCOSDA/CASLRE), pp.1-8, 2013. ,
DOI : 10.1109/ICSDA.2013.6709851
Perceptual and objective detection of discontinuities in concatenative speech synthesis, 2001 IEEE International Conference on Acoustics, Speech, and Signal Processing. Proceedings (Cat. No.01CH37221), pp.837-840, 2001. ,
DOI : 10.1109/ICASSP.2001.941045
Modelling F0 Dynamics in??Unit??Selection??Based??Speech??Synthesis, Proc. of TSD, pp.457-464, 2014. ,
DOI : 10.1007/978-3-319-10816-2_55
Natural-sounding speech synthesis using variable-length units, 1998. ,
Vocalic sandwich, a unit designed for unit selection TTS, Proc. of Interspeech, pp.2079-2082, 2009. ,
espeak text to speech, 2012. ,
Automatic phonetic transcription of non-prompted speech, Proc. ICPhS, p.607610, 1999. ,
ROOTS: a toolkit for easy, fast and consistent processing of large sequential annotated data collections, Proc. of LREC, pp.619-626, 2014. ,
URL : https://hal.archives-ouvertes.fr/hal-00974628
Unit Selection Cost Function Exploration Using an A* Based Text-to-Speech System, Proc. of TSD, pp.432-440, 2014. ,
DOI : 10.1007/978-3-319-10816-2_52
URL : https://hal.archives-ouvertes.fr/hal-01133321
Concatenation cost calculation and optimisation for unit selection in TTS, IEEE Workshop on Speech Synthesis, pp.0-3, 2002. ,
Efficient and reliable perceptual weight tuning for unit-selection text-to-speech synthesis based on active interactive genetic algorithms: A proof-of-concept, Speech Communication, vol.53, issue.5, pp.786-800, 2011. ,
DOI : 10.1016/j.specom.2011.01.004
High Quality TTS Voices Within One Day A new distance measure for costing spectral discontinuities in concatenative speech synthesizers, Seventh ISCA Workshop on Speech Synthesis ITRW, 2001. ,
Natural-sounding speech synthesis using variable-length units, Proc. of ICSLP, 1998. ,
The IRISA Text-To-Speech System for the Blizzard Challenge Available: https, Blizzard Challenge 2015 Workshop, 2015. ,
On the Suitability of Vocalic Sandwiches in a Corpus-Based TTS Engine, Interspeech 2016, 2016. ,
DOI : 10.21437/Interspeech.2016-1222
URL : https://hal.archives-ouvertes.fr/hal-01338839
Random forests, Machine Learning, vol.45, issue.1, pp.5-32, 2001. ,
DOI : 10.1023/A:1010933404324
Scikit-learn: Machine learning in Python, Journal of Machine Learning Research, vol.12, pp.2825-2830, 2011. ,
URL : https://hal.archives-ouvertes.fr/hal-00650905