Demo of Idlak Tangle, An Open Source DNN-Based Parametric Speech Synthesiser

Blaise Potard, Matthew Aylett, David A. Braude, Petr Motlicek

Research output: Chapter in Book/Report/Conference proceedingConference contribution


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
Original languageEnglish
Title of host publication9th ISCA Speech Synthesis Workshop
PublisherInternational Speech Communication Association
Number of pages1
Publication statusPublished - 12 Sep 2016
EventInterspeech 2016 - San Francisco, United States
Duration: 8 Sep 201612 Sep 2016


ConferenceInterspeech 2016
Country/TerritoryUnited States
CitySan Francisco
Internet address


Dive into the research topics of 'Demo of Idlak Tangle, An Open Source DNN-Based Parametric Speech Synthesiser'. Together they form a unique fingerprint.

Cite this