The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
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.
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Cites
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Cited by
A Lip Sync Expert Is All You Need for Speech to Lip Generation In the Wild
Prajwal, K. R., Mukhopadhyay, R., Namboodiri, V. P., & Jawahar, C. V. (2020) · Proceedings of the 28th ACM International Conference on Multimedia · doi:10.1145/3394171.3413532 · Cited by 897
Deep Audio-Visual Speech Recognition
Afouras, T., Chung, J. S., Senior, A., Vinyals, O., & Zisserman, A. (2022) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2018.2889052 · Cited by 801
Audio-Visual Scene Analysis with Self-Supervised Multisensory Features
Owens, A., & Efros, A. A. (2018) · Lecture Notes in Computer Science · doi:10.1007/978-3-030-01231-1_39 · Cited by 704
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Multimodal intelligence: Representation learning, information fusion, and applications
Zhang, C., Yang, Z., He, X., & Deng, L. (2020) · IEEE Journal of Selected Topics in Signal Processing · doi:10.1109/jstsp.2020.2987728 · Cited by 511
Metadata
- Authors
- Cooke, M., Barker, J., Cunningham, S., & Shao, X.
- Venue
- The Journal of the Acoustical Society of America
- Publisher
- Acoustical Society of America (ASA)
- Published
- 2006-11-01
- Volume
- 120
- Issue
- 5
- Pages
- 2421-2424
- ISSN
- 0001-4966 (ISSN-L)
- 1520-8524
- OpenAlex
- W2015143272
- Cited by
- 1,144
- References
- 1
- FWCI
- 25.64
- Type
- journal article
- Language
- en
- Open access
- closed
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- Cooke, M., Barker, J., Cunningham, S., & Shao, X. (2006). An audio-visual corpus for speech perception and automatic speech recognition. The Journal of the Acoustical Society of America. https://doi.org/10.1121/1.2229005
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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