All Outputs (3)

A Novel Frame Structure for Cloud-Based Audio-Visual Speech Enhancement in Multimodal Hearing-aids (2022)
Presentation / Conference Contribution
Bishnu, A., Gupta, A., Gogate, M., Dashtipour, K., Adeel, A., Hussain, A., Sellathurai, M., & Ratnarajah, T. (2022, October). A Novel Frame Structure for Cloud-Based Audio-Visual Speech Enhancement in Multimodal Hearing-aids. Presented at 2022 IEEE International Conference on E-health Networking, Application & Services (HealthCom), Genoa, Italy

In this paper, we design a first of its kind transceiver (PHY layer) prototype for cloud-based audio-visual (AV) speech enhancement (SE) complying with high data rate and low latency requirements of future multimodal hearing assistive technology. The... Read More about A Novel Frame Structure for Cloud-Based Audio-Visual Speech Enhancement in Multimodal Hearing-aids.

Towards real-time privacy-preserving audio-visual speech enhancement (2022)
Presentation / Conference Contribution
Gogate, M., Dashtipour, K., & Hussain, A. (2022, September). Towards real-time privacy-preserving audio-visual speech enhancement. Presented at 2nd Symposium on Security and Privacy in Speech Communication, Incheon, Korea

Human auditory cortex in everyday noisy situations is known to exploit aural and visual cues that are contextually combined by the brain’s multi-level integration strategies to selectively suppress the background noise and focus on the target speaker... Read More about Towards real-time privacy-preserving audio-visual speech enhancement.

A Novel Speech Intelligibility Enhancement Model based on Canonical Correlation and Deep Learning (2022)
Presentation / Conference Contribution
Hussain, T., Diyan, M., Gogate, M., Dashtipour, K., Adeel, A., Tsao, Y., & Hussain, A. (2022, July). A Novel Speech Intelligibility Enhancement Model based on Canonical Correlation and Deep Learning. Presented at 2022 44th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC), Glasgow, Scotland

Current deep learning (DL) based approaches to speech intelligibility enhancement in noisy environments are often trained to minimise the feature distance between noise-free speech and enhanced speech signals. Despite improving the speech quality, su... Read More about A Novel Speech Intelligibility Enhancement Model based on Canonical Correlation and Deep Learning.