| 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 | 49 | 2016 |
| 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 | 41 | 2016 |
| 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 | 32 | 2014 |
| 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 | 20 | 2015 |
| 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 | 16 | 2014 |
| 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 | 12 | 2015 |
| Investigating the shortcomings of HMM synthesis T Merritt, S King Eighth ISCA Workshop on Speech Synthesis, 2013 | 11 | 2013 |
| 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 | 9 | 2014 |
| Expressive speech synthesis for storytelling: the INNOETICS’entry to the blizzard challenge 2016 S Raptis, P Tsiakoulis, A Chalamandaris, S Karabetsos Proc. Blizzard Challenge workshop, 2016 | 8 | 2016 |
| Robust universal neural vocoding J Lorenzo-Trueba, T Drugman, J Latorre, T Merritt, B Putrycz, ... arXiv preprint arXiv:1811.06292, 2018 | 6 | 2018 |
| 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 | 5 | 2018 |
| 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 | 3 | 2019 |
| 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 | 3 | 2015 |
| 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 | 2 | 2017 |
| Analysing Shortcomings of Statistical Parametric Speech Synthesis GE Henter, S King, T Merritt, G Degottex arXiv preprint arXiv:1807.10941, 2018 | 1 | 2018 |
| Overcoming the limitations of statistical parametric speech synthesis T Merritt The University of Edinburgh, 2017 | 1 | 2017 |
| 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 | | 2019 |
| Listening test materials for" Deep neural network context embeddings for model selection in rich-context HMM synthesis" T Merritt University of Edinburgh. The Centre for Speech Technology Research (CSTR), 2015 | | 2015 |
| TOWARDS ACHIEVING ROBUST UNIVERSAL NEURAL VOCODING J Lorenzo-Trueba, T Drugman, J Latorre, T Merritt, B Putrycz, ... | | |
| Readme for REHASP 0.5: The REpeated HArvard Sentence Prompts corpus version 0.5 GE Henter, T Merritt, M Shannon, C Mayo, S King | | |
Simon KingProfessor of Speech Processing, University of EdinburghVerified email at ed.ac.uk
