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# GRID
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GRID is 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.
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# GRID
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GRID is 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.
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# Link
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- Proposed by the article [An audio-visual corpus for speech perception and automatic speech recognition](https://pubs.aip.org/asa/jasa/article-abstract/120/5/2421/934379/An-audio-visual-corpus-for-speech-perception-and?redirectedFrom=fulltext)
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- Used in VisualTTS field by the CVPR2020 article [Learning Individual Speaking Styles for Accurate Lip to Speech Synthesis](https://openaccess.thecvf.com/content_CVPR_2020/papers/Prajwal_Learning_Individual_Speaking_Styles_for_Accurate_Lip_to_Speech_Synthesis_CVPR_2020_paper.pdf)
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- [Github Page](https://github.com/Rudrabha/Lip2Wav?tab=readme-ov-file)
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