@InProceedings{Howard2018_428,
author = {Ian S. Howard and Peter Birkholz},
booktitle = {Studientexte zur Sprachkommunikation: Elektronische Sprachsignalverarbeitung 2018},
title = {Using state feedback to control an articulatory synthesizer},
year = {2018},
editor = {André Berton and Udo Haiber and Wolfgang Minker},
month = mar,
pages = {351--358},
publisher = {TUDpress, Dresden},
abstract = {Here we consider the application of state feedback control to stabilize an
articulatory speech synthesizer during the generation of speech utterances. We first
describe the architecture of such an approach from a signal flow perspective. We
explain that an internal model is needed for effective operation, which can be
acquired during a babbling phase. The required inverse mapping between the
synthesizer’s control parameters and their auditory consequences can be learned
using a neural network. Such an inverse model provides a means to map output that
occur in an acoustic speech domain back to an articulatory domain, where it can
assist in compensatory adjustments. We show that it is possible to build such an
inverse model for the Birkholz articulatory synthesizer for vowel production. Finally,
we illustrate the operation of the inverse model with some simple vowels sequences
and static vowel qualities.},
isbn = {978-3-959081-28-3},
issn = {0940-6832},
keywords = {Speech Synthesis},
url = {https://www.essv.de/pdf/pdf/2018_351_358.pdf},
}