Thomas Merritt
Thomas Merritt
Amazon
Verified email at amazon.co.uk
Title
Cited by
Cited by
Year
From HMMs to DNNs: where do the improvements come from?
O Watts, GE Henter, T Merritt, Z Wu, S King
2016 IEEE International Conference on Acoustics, Speech and Signal …, 2016
622016
Deep neural network-guided unit selection synthesis
T Merritt, RAJ Clark, Z Wu, J Yamagishi, S King
2016 IEEE International Conference on Acoustics, Speech and Signal …, 2016
512016
Measuring the perceptual effects of modelling assumptions in speech synthesis using stimuli constructed from repeated natural speech
GE Henter, T Merritt, M Shannon, C Mayo, S King
Fifteenth Annual Conference of the International Speech Communication …, 2014
402014
Attributing modelling errors in HMM synthesis by stepping gradually from natural to modelled speech
T Merritt, J Latorre, S King
2015 IEEE International Conference on Acoustics, Speech and Signal …, 2015
222015
Investigating source and filter contributions, and their interaction, to statistical parametric speech synthesis
T Merritt, T Raitio, S King
Fifteenth Annual Conference of the International Speech Communication …, 2014
192014
Effect of data reduction on sequence-to-sequence neural tts
J Latorre, J Lachowicz, J Lorenzo-Trueba, T Merritt, T Drugman, ...
ICASSP 2019-2019 IEEE International Conference on Acoustics, Speech and …, 2019
152019
Investigating the shortcomings of HMM synthesis
T Merritt, S King
Eighth ISCA Workshop on Speech Synthesis, 2013
152013
Towards achieving robust universal neural vocoding
J Lorenzo-Trueba, T Drugman, J Latorre, T Merritt, B Putrycz, ...
arXiv preprint arXiv:1811.06292, 2018
132018
Robust universal neural vocoding
J Lorenzo-Trueba, T Drugman, J Latorre, T Merritt, B Putrycz, ...
arXiv preprint arXiv:1811.06292, 2018
132018
Deep neural network context embeddings for model selection in rich-context HMM synthesis
T Merritt, J Yamagishi, Z Wu, O Watts, S King
Sixteenth Annual Conference of the International Speech Communication …, 2015
132015
Expressive speech synthesis for storytelling: the INNOETICS’entry to the blizzard challenge 2016
S Raptis, P Tsiakoulis, A Chalamandaris, S Karabetsos
Proc. Blizzard Challenge, 2016
102016
A flexible front-end for HTS
MP Aylett, R Dall, A Ghoshal, GE Henter, T Merritt
Fifteenth Annual Conference of the International Speech Communication …, 2014
92014
Phrase Break Prediction for Long-Form Reading TTS: Exploiting Text Structure Information.
V Klimkov, A Nadolski, A Moinet, B Putrycz, R Barra-Chicote, T Merritt, ...
Interspeech, 1064-1068, 2017
82017
In other news: A bi-style text-to-speech model for synthesizing newscaster voice with limited data
N Prateek, M Łajszczak, R Barra-Chicote, T Drugman, J Lorenzo-Trueba, ...
arXiv preprint arXiv:1904.02790, 2019
62019
Comprehensive evaluation of statistical speech waveform synthesis
T Merritt, B Putrycz, A Nadolski, T Ye, D Korzekwa, W Dolecki, T Drugman, ...
2018 IEEE Spoken Language Technology Workshop (SLT), 325-331, 2018
62018
Listening test materials for
T Merritt, J Yamagishi, Z Wu, O Watts, S King
Deep neural network context embeddings for model selection in rich-context …, 2015
52015
Analysing Shortcomings of Statistical Parametric Speech Synthesis
GE Henter, S King, T Merritt, G Degottex
arXiv preprint arXiv:1807.10941, 2018
22018
Overcoming the limitations of statistical parametric speech synthesis
T Merritt
The University of Edinburgh, 2017
22017
Contextual text-to-speech processing
RB Chicote, J Latorre, AF Nadolski, V Klimkov, TE Merritt
US Patent App. 16/665,886, 2020
2020
Contextual text-to-speech processing
RB Chicote, J Latorre, AF Nadolski, V Klimkov, TE Merritt
US Patent 10,475,438, 2019
2019
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