activity
20172021
most citedPhoneme-to-viseme mappings: the good, the bad, and the ugly

59 citations · 115 across the 19 of their papers we have counts for

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Showing 2017Show all

10 papers · 1 filter

cs.CV2017

Understanding the visual speech signal

Helen L Bear

For machines to lipread, or understand speech from lip movement, they decode lip-motions (known as visemes) into the spoken sounds. We investigate the visual speech channel to furt…

cs.CV2017★ 5 cited

Visual gesture variability between talkers in continuous visual speech

Helen L Bear

Recent adoption of deep learning methods to the field of machine lipreading research gives us two options to pursue to improve system performance. Either, we develop end-to-end sys…

cs.CV2017★ 3 cited

Visual speech recognition: aligning terminologies for better understanding

Helen L Bear, Sarah Taylor

We are at an exciting time for machine lipreading. Traditional research stemmed from the adaptation of audio recognition systems. But now, the computer vision community is also par…

cs.CV2017

Decoding visemes: improving machine lipreading

Helen L Bear

Machine lipreading (MLR) is speech recognition from visual cues and a niche research problem in speech processing & computer vision. Current challenges fall into two groups: the co…

cs.CV2017

Decoding visemes: improving machine lipreading

Helen L. Bear, Richard Harvey

To undertake machine lip-reading, we try to recognise speech from a visual signal. Current work often uses viseme classification supported by language models with varying degrees o…

cs.CV2017★ 11 cited

Finding phonemes: improving machine lip-reading

Helen L. Bear, Richard W. Harvey, Yuxuan Lan

In machine lip-reading there is continued debate and research around the correct classes to be used for recognition. In this paper we use a structured approach for devising speaker…

cs.CV2017★ 1 cited

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

Helen L. Bear, Stephen J. Cox, Richard W. Harvey

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,…

cs.CV2017★ 1 cited

Which phoneme-to-viseme maps best improve visual-only computer lip-reading?

Helen L. Bear, Richard W. Harvey, Barry-John Theobald +1

A critical assumption of all current visual speech recognition systems is that there are visual speech units called visemes which can be mapped to units of acoustic speech, the pho…

cs.CV2017

Some observations on computer lip-reading: moving from the dream to the reality

Helen L. Bear, Gari Owen, Richard Harvey +1

In the quest for greater computer lip-reading performance there are a number of tacit assumptions which are either present in the datasets (high resolution for example) or in the m…

cs.CV2017

Resolution limits on visual speech recognition

Helen L. Bear, Richard Harvey, Barry-John Theobald +1

Visual-only speech recognition is dependent upon a number of factors that can be difficult to control, such as: lighting; identity; motion; emotion and expression. But some factors…