  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 of success. A few recent works suggest phoneme
classification, in the right circumstances, can outperform viseme
classification. In this work we present a novel two-pass method of training
phoneme classifiers which uses previously trained visemes in the first pass.
With our new training algorithm, we show classification performance which
significantly improves on previous lip-reading results.
