About AMHAT 2023

Hearing loss affects 1.5 billion people globally and is associated with poorer health and social outcomes. Recent technological advances have enabled low-latency, high data-rate wireless solutions for in-ear hearing assistive devices, which have primarily reformed the current innovation direction of the hearing industry.

Nevertheless, even sophisticated commercial hearing aids and cochlear-implant devices are based on audio-only processing, and remain ineffective in restoring speech intelligibility in overwhelmingly noisy environments. Human performance in such situations is known to be dependent upon input from both the aural and visual senses that are then combined by sophisticated multi-level integration strategies in the brain. Due to advances in miniaturized sensors and embedded low-power technology, we now have the potential to monitor not only sound but also many parameters such as visuals to improve speech intelligibility. Creating future transformative multimodal hearing assistive technologies that draw on cognitive principles of normal (visually-assisted) hearing, raises a range of formidable technical, privacy and usability challenges which need to be holistically overcome.

The AMHAT Workshop aims to provide an interdisciplinary forum for the wider speech signal processing, artificial intelligence, wireless sensing and communications and hearing technology communities to discuss the latest advances in this emerging field, and stimulate innovative research directions, including future challenges and opportunities.

Workshop Chairs

Amir Hussain, Edinburgh Napier University, UK
Mathini Sellathurai, Heriot-Watt University, UK
Peter Bell, University of Edinburgh, UK
Katherine August, Stevens Institute of Technology, USA

Steering Committee Chairs

John Hansen, University of Texas at Dallas, USA
Naomi Harte, Trinity College Dublin, UK
Michael Akeroyd, University of Nottingham, UK

Scientific Committee Chair

Yu Tsao, Academia Sinica, Taiwan

Scientific Committee

Peter Derleth, Sonova
Ben Milner, University of East Anglia, UK
Jennifer Williams, University of Southampton, UK
Emanuel Habets, University of Erlangen-Nuremberg, Germany
Chi-Chun Lee, National Tsing Hua University, Taiwan
Hadi Larijani, Glasgow Caledonian University, UK
Erfan Loweimi, University of Cambridge and Edinburgh Napier University, UK
Raza Varzandeh, University of Oldenburgh, Germany
Jesper Jesper, Aalborg University, Denmark
Yong Xu, Tencent America, USA
Dong Yu, Tencent AI Lab, China
Daniel Michelsanti, Aalborg University, Denmark
Volker Hohmann, University of Oldenburgh, Germany
Marc Delcroix, NTT Communication Science Laboratories, Japan
Zheng-Hua Tan, Aalborg University, Denmark
Harish Chandra Dubey, Microsoft, USA
Simon Doclo, University of Oldenburgh, Germany
Kia Dashtipour, Edinburgh Napier University
Hsin-Min Wang, Academia Sinica, Taiwan
Mandar Gogate, Edinburgh Napier University, UK
Jun-Cheng Chen, Academia Sinica, Taiwan
Adeel Ahsan, University of Wolverhampton, UK
Alex Casson, University of Manchester, UK
Tharm Ratnarajah, University of Edinburgh, UK
Jen-Cheng Hou, Academia Sinica, Taiwan
Tughrul Arslan, University of Edinburgh, UK
Shinji Watanabe, Carnegie Mellon University
Nima Mesgarani, Columbia University, USA
Jesper Jensen, Aalborg University, Denmark
Qiang Huang, University of Sunderland, UK
Bernd T. Meyer, University of Oldenburgh, Germany

Topics of interest

The Workshop invites authors to submit papers presenting novel research related to all aspects of multi-modal hearing assistive technologies, including, but not limited to the following:

  1. Novel explainable and privacy-preserving machine learning and statistical model based approaches to multi-modal speech-in-noise processing
  2. End-to-end real-time, low-latency and energy-efficient audio-visual speech enhancement and separation methods
  3. Human auditory-inspired models of multi-modal speech perception and enhancement
  4. Internet of things (IoT), 5G/6G and wireless sensing enabled approaches to multi-modal hearing assistive technologies
  5. Multi-modal speech enhancement and separation in AR/VR environments
  6. Innovative binaural and multi-microphone, including MEMS antenna integration and multi-modal beamforming approaches
  7. Cloud, Edge and System-on-Chip based software and hardware implementations
  8. New multi-modal speech intelligibility models for normal and hearing-impaired listeners
  9. Audio-visual speech quality and intelligibility assessment and prediction techniques for multi-modal hearing assistive technologies
  10. Demonstrators of multi-modal speech-enabled hearing assistive technology use cases (e.g. multi-modal listening and communication devices)
  11. Accessibility and human-centric factors in the design and evaluation of multi-modal hearing assistive technology, including public perceptions, ethics, standards, societal, economic and political impacts
  12. Contextual (e.g. user preference and cognitive load-aware) multi-modal hearing assistive technologies
  13. Innovative applications of multi-modal hearing assistive technologies (e.g. diagnostics, therapeutics, human-robot interaction, sign-language recognition for aided communication)
  14. Live demonstrators of multi-modal speech-enabled hearing assistive technology use cases (e.g. multi-modal cochlear implants and listening and communication devices)
  15. Accessibility and human-centric factors in the design and evaluation of multi-modal hearing assistive technology, including public perceptions, ethics, standards, societal, economic and political impacts

Important Dates

Workshop Paper Submission Deadline: 23 March 2023 24 February 2023
Workshop Paper Acceptance Notification: 14 April 2023
Workshop Camera Ready Paper Deadline: 28 April 2023
All deadlines are 11:59PM UTC-12:00 ("anywhere on Earth").

Paper Submission Guidelines

The AMHAT workshop accepts both short (2 pages) and long paper (4 pages) submissions on topics as highlighted in Topics of interest. Papers may be no longer than 5 pages, including all text, figures, and references, and the 5th page may contain only references. All submissions should follow the ICASSP-2023 paper style and format (https://2023.ieeeicassp.org/paper-submission-guidelines/). Only long papers will be published in IEEE Xplore.

Paper submission now open!

Note: The peer-reviewing process will follow the main conference reviewing guidelines and all accepted Workshop papers will be published in the IEEE Xplore Digital Library. Note that, like the main conference, the AMHAT Workshop is fostering return to an in-person attendance experience. Accordingly, there must be an author of each accepted workshop paper presenting it in-person.

Keynote speakers

Prof Yu Tsao, Academia Sinica, Taiwan

Towards Audio-visual Speech Enhancement in Real-World Scenarios

We propose a novel audio-visual speech enhancement (AVSE) algorithm, iLAVSE, for a real-world scenario. Compared to conventional AVSE systems, iLAVSE overcomes three common issues that can occur in a real-world environment: the additional cost of processing visual data, audio-visual asynchronization, and low-quality visual data. To evaluate iLAVSE, we use a multimodal Taiwan-Mandarin speech with video dataset and compare with conventional AVSE systems. The results demonstrate that iLAVSE can effectively address the aforementioned issues and improve speech enhancement performance, making it suitable for real-world applications.

Dr Peter Derleth, Sonova AG

Technological and commercial aspects of assistive hearing solutions

Assistive hearing solutions come in a variety of form factors, are designed to serve various use cases, are targeted at different user groups and distributed to the market as consumer or medical products. Each of the mentioned aspects influences if a technological/functional innovation reaches the respective market segment and gets the chance to improve the daily life of human listeners. The presentation will shed a light on existing and near future hearing aid technology and share anecdotal insights into alternative technical solutions which did not reach a high market impact despite being technically advanced.