This paper introduces incoming evaluation frameworks for bimodal speech recognition in noisy conditions and real environments. In order to develop a robust speech recognition in noisy environments, bimodal speech recognition which uses acoustic and visual information has been paid attention to particularly for this decade. As a lot of methods and techniques for bimodal speech recognition have been proposed, a common evaluation framework, including audio-visual speech data and baseline system, is needed to estimate and compare these techniques and bimodal speech recognition schemes. Audio-visual evaluation frameworks, CENSREC-1-AV and CENSREC-2-AV, have been being built by the CENSREC project in Japan; CENSREC- 1-AV includes artificially noise-added waveforms and image sequences, whereas CENSREC-2-AV consists of audio-visual data recorded in in-car environments. A baseline method and its recognition results will be also provided with these corpora.

Index Terms: evaluation framework, audio-visual speech corpus, bimodal speech recognition, noisy environments.