Now showing items 1-7 of 7
Modelling the uncertainty in recovering articulation from acoustics
This paper presents an experimental comparison of the performance of the multilayer perceptron (MLP) with that of the mixture density network (MDN) for an acoustic-to-articulatory mapping task. A corpus of acoustic-articulatory ...
Multisyn voices from ARCTIC data for the Blizzard challenge.
(International Speech Communication Association, 2005)
This paper describes the process of building unit selection voices for the Festival Multisyn engine using four ARCTIC datasets, as part of the Blizzard evaluation challenge. The build process is almost entirely automatic, ...
An Automatic Speech Recognition System Using Neural Networks and Linear Dynamic Models to Recover and Model Articulatory Traces
(International Speech Communication Association, 2000-10)
We describe a speech recognition system which uses articulatory parameters as basic features and phone-dependent linear dynamic models. The system first estimates articulatory trajectories from the speech signal. Estimations ...
Speech recognition via phonetically-featured syllables
(University of the Saarland, 2000)
We describe recent work on two new automatic speech recognition systems. The first part of this paper describes the components of a system based on phonological features (which we call Espresso-P) in which the values of ...
Festival 2 – Build Your Own General Purpose Unit Selection Speech Synthesiser
This paper describes version 2 of the Festival speech synthesis system. Festival 2 provides a development environment for concatenative speech synthesis, and now includes a general purpose unit selection speech synthesis ...
Speech production knowledge in automatic speech recognition
Although much is known about how speech is produced, and research into speech production has resulted in measured articulatory data, feature systems of different kinds and numerous models, speech production knowledge is ...
Estimating articulatory parameters from the acoustic speech signal
(The University of Edinburgh, 2002)