Speaker-independent machine lip-reading with speaker-dependent viseme classifiers

10/03/2017
by   Helen L Bear, et al.
0

In machine lip-reading, which is identification of speech from visual-only information, there is evidence to show that visual speech is highly dependent upon the speaker [1]. Here, we use a phoneme-clustering method to form new phoneme-to-viseme maps for both individual and multiple speakers. We use these maps to examine how similarly speakers talk visually. We conclude that broadly speaking, speakers have the same repertoire of mouth gestures, where they differ is in the use of the gestures.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
05/08/2018

Comparing heterogeneous visual gestures for measuring the diversity of visual speech signals

Visual lip gestures observed whilst lipreading have a few working defini...
research
10/03/2017

Decoding visemes: improving machine lipreading (PhD thesis)

Machine lipreading (MLR) is speech recognition from visual cues and a ni...
research
10/03/2017

Finding phonemes: improving machine lip-reading

In machine lip-reading there is continued debate and research around the...
research
06/21/2019

Unsupervised Phoneme and Word Discovery from Multiple Speakers using Double Articulation Analyzer and Neural Network with Parametric Bias

This paper describes a new unsupervised machine learning method for simu...
research
09/18/2019

RTTD-ID: Tracked Captions with Multiple Speakers for Deaf Students

Students who are deaf and hard of hearing cannot hear in class and do no...
research
10/03/2017

Visual gesture variability between talkers in continuous visual speech

Recent adoption of deep learning methods to the field of machine lipread...
research
04/12/2017

Trainable Referring Expression Generation using Overspecification Preferences

Referring expression generation (REG) models that use speaker-dependent ...

Please sign up or login with your details

Forgot password? Click here to reset