What is ASPIRE? ASPIRE is a a first of its kind, audiovisual speech corpus recorded in real noisy environment (such as cafe, restaurants) which can be used to support reliable evaluation of multi-modal Speech Filtering technologies. This dataset follows the same sentence format as the audio-visual Grid corpus. The recorded audiovisual speech corpus can be used for reliable evaluation of next generation multi-modal Speech Filtering technologies. Citing the corpus @article{gogate2020cochleanet, title={CochleaNet: A robust language-independent audio-visual model for real-time speech enhancement}, author={Gogate, Mandar and Dashtipour, Kia and Adeel, Ahsan and Hussain, Amir}, journal={Information Fusion}, volume={63}, pages={273--285}, year={2020}, publisher={Elsevier} } OR Gogate, M., Dashtipour, K., Adeel, A., & Hussain, A. (2020). CochleaNet: A robust language-independent audio-visual model for real-time speech enhancement. Information Fusion, 63, 273-285. Acknowledgements This research was funded by the UK Engineering and Physical Sciences Research Council (EPSRC project AV-COGHEAR, EP/M026981/1)

{"references": ["Mandar Gogate, Kia Dashtipour, Ahsan Adeel, Amir Hussain, CochleaNet: A robust language-independent audio-visual model for real-time speech enhancement, Information Fusion, Volume 63, 2020, Pages 273-285, ISSN 1566-2535, https://doi.org/10.1016/j.inffus.2020.04.001."]}