title: An audio-visual corpus for speech perception and automatic speech recognition.
abstract: An audio-visual corpus has been collected to support the use of common material in speech perception and automatic speech recognition studies. The corpus consists of high-quality audio and video recordings of 1000 sentences spoken by each of 34 talkers. Sentences are simple, syntactically identical phrases such as "place green at B 4 now". Intelligibility tests using the audio signals suggest that the material is easily identifiable in quiet and low levels of stationary noise. The annotated corpus is available on the web for research use.
authors.affiliation: Department of Computer Science, University of Sheffield, Regent Court, 211 Portobello Street, Sheffield, S1 4DP, United Kingdom. m.cooke@dcs.shef.ac.uk
authors.forename: Martin
authors.initials: M
authors.lastname: Cooke
authors.forename: Jon
authors.initials: J
authors.lastname: Barker
authors.forename: Stuart
authors.initials: S
authors.lastname: Cunningham
authors.forename: Xu
authors.initials: X
authors.lastname: Shao
mesh_terms: D000161:Acoustic Stimulation; D000293:Adolescent; D000328:Adult; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D009622:Noise; D013067:Speech Perception / Q000502:physiology*; D013069:Speech Reception Threshold Test; D013637:Tape Recording; D014741:Video Recording