This paper presents a text to speech (TTS) extension to Kaldi —
a liberally licensed open source speech recognition system. The system,
Idlak Tangle, uses recent deep neural network (DNN) methods for modelling
speech, the Idlak XML based text processing system as the front end,
and a newly released open source mixed excitation MLSA vocoder included
in Idlak. The system has none of the licensing restrictions of current
freely available HMM style systems, such as the HTS toolkit. To date
no alternative open source DNN systems are available. Tangle combines
the Idlak front-end and vocoder, with two DNNs modelling respectively
the units duration and acoustic parameters, providing a fully functional
end-to-end TTS system.
Experimental results using
the freely available SLT speaker from CMU ARCTIC, reveal that the speech
output is rated in a MUSHRA test as significantly more natural than
the output of HTS-demo, the only other free to download HMM system
available with no commercially restricted or proprietary IP. The tools,
audio database and recipe required to reproduce the results presented
in these paper are fully available online.
Cite as: Potard, B., Aylett, M.P., Baude, D.A., Motlicek, P. (2016) Idlak Tangle: An Open Source Kaldi Based Parametric Speech Synthesiser Based on DNN. Proc. Interspeech 2016, 2293-2297, doi: 10.21437/Interspeech.2016-1188
@inproceedings{potard16_interspeech,
author={Blaise Potard and Matthew P. Aylett and David A. Baude and Petr Motlicek},
title={{Idlak Tangle: An Open Source Kaldi Based Parametric Speech Synthesiser Based on DNN}},
year=2016,
booktitle={Proc. Interspeech 2016},
pages={2293--2297},
doi={10.21437/Interspeech.2016-1188}
}