Glove-Talk II: A Neural Network Interface Which Maps
Gestures to Parallel Formant Speech Synthesizer Controls
Sidney Fels and Geoffrey Hinton
Department of Computer Science
University of Toronto & University of Toronto
Toronto, ON, Canada, M5S 1A4
Abstract
Glove-Talk-II is a system which translates hand gestures to speech
through an adaptive interface. Hand gestures are mapped continuously to 10 control
parameters of a parallel formant speech synthesizer. The mapping allows the hand to act as
an artificial vocal tract that produces speech in real time. This gives an unlimited
vocabulary, multiple languages in addition to direct control of fundamental frequency and
volume. Currently, the best version of Glove-TalkII uses several input devices (including
a Cyberglove, a Contact Glove, a polhemus sensor, and a foot-pedal), a parallel formant
speech synthesizer and 3 neural networks. The gesture-to-speech task is divided into vowel
and consonant production by using a gating network to weight the outputs of a vowel and a
consonant neural network. The gating network and the consonant network are trained with
examples from the user. The vowel network implements a fixed, user-defined relationship
between hand-position and vowel sound and does not require any training examples from the
user. Volume, fundamental frequency and stop consonants are produced with a fixed mapping
from the input devices. One subject has trained for about 100 hours to speak intelligibly
with Glove-TalkII. He passed through eight distinct stages while learning to speak. He
speaks slowly with speech quality similar to a text-to-speech synthesizer but with far
more natural-sounding pitch variations.
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