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<div dir="auto"><span style="font-family: Calibri, sans-serif; font-size: 9pt; color: rgb(0, 0, 0);">Dear connectionists (with apologies for any cross-postings) </span><br>
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<span style="font-family: Calibri, sans-serif; font-size: 9pt; color: rgb(0, 0, 0);">We are pleased to announce the third edition of the International Challenge on audio-visual speech enhancement (AVSEC-3) as a Satellite Workshop of 2024 INTERSPEECH on 1st
September 2024, at Kos Island, Greece (submissions deadline 20 June 2024 - see details below and here: </span><span style="font-family: Calibri, sans-serif; font-size: 9pt; color: rgb(70, 120, 134);"><a href="http://challenge.cogmhear.org/" id="OWAe3ed5d44-3155-1290-9477-9314b1a4e4e1" class="OWAAutoLink" data-loopstyle="linkonly" style="text-decoration: none; margin-top: 0px; margin-bottom: 0px; color: rgb(70, 120, 134);">http://challenge.cogmhear.org</a></span><span style="font-family: Calibri, sans-serif; font-size: 9pt; color: rgb(0, 0, 0);">). </span></p>
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<span style="font-family: Calibri, sans-serif; font-size: 9pt; color: rgb(0, 0, 0);">Contributions are also invited to the related Special Issue of the IEEE Journal of Selected Topics in Signal Processing (JSTSP) on "Deep Multimodal Speech Enhancement and Separation"
(paper submission deadline: 30 Sep 2024 - see CFP below and here: <a rel="noreferrer noopener" href="https://signalprocessingsociety.org/publications-resources/special-issue-deadlines/ieee-jstsp-special-issue-deep-multimodal-speech-enhancement-and-separation..">
https://signalprocessingsociety.org/publications-resources/special-issue-deadlines/ieee-jstsp-special-issue-deep-multimodal-speech-enhancement-and-separation</a>) </span></p>
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<span style="font-family: Calibri, sans-serif; font-size: 9pt; font-weight: 700; color: rgb(0, 0, 0);">AVSEC-3 Workshop: Important Dates</span><span style="font-family: Calibri, sans-serif; font-size: 9pt; color: rgb(0, 0, 0);">:</span></p>
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<span style="font-family: Calibri, sans-serif; font-size: 9pt; color: rgb(0, 0, 0);">16th February 2024: Release of training and development data. </span></p>
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<span style="font-family: Calibri, sans-serif; font-size: 9pt; color: rgb(0, 0, 0);">22nd March 2024: Release of low-latency baseline system. </span></p>
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<span style="font-family: Calibri, sans-serif; font-size: 9pt; color: rgb(0, 0, 0);">10th April 2024: Evaluation data release. </span></p>
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<span style="font-family: Calibri, sans-serif; font-size: 9pt; color: rgb(0, 0, 0);">10th April 2024: Leaderboard open for submissions. </span></p>
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<span style="font-family: Calibri, sans-serif; font-size: 9pt; color: rgb(0, 0, 0);">6th May 2024: Paper submission opens. </span></p>
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<span style="font-family: Calibri, sans-serif; font-size: 9pt; font-weight: 700; color: rgb(0, 0, 0);">20th June/2024: Deadline for challenge submissions.</span></p>
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<span style="font-family: Calibri, sans-serif; font-size: 9pt; font-weight: 700; color: rgb(0, 0, 0);">28th June 2024: Paper submission closes. </span></p>
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<span style="font-family: Calibri, sans-serif; font-size: 9pt; color: rgb(0, 0, 0);">12th July: Acceptance notification. </span></p>
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<span style="font-family: Calibri, sans-serif; font-size: 9pt; color: rgb(0, 0, 0);">26th July: early release of evaluation results.</span></p>
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<span style="font-family: Calibri, sans-serif; font-size: 9pt; color: rgb(0, 0, 0);">1st August 2024: camera-ready paper. </span></p>
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<span style="font-family: Calibri, sans-serif; font-size: 9pt; color: rgb(0, 0, 0);">The AVSEC Challenge sets the first benchmark in the field by providing a carefully crafted dataset and scalable protocol for human listening evaluation of audio-visual speech
enhancement systems. The open AVSEC framework aims to foster collaborative research and innovation to facilitate the development and evaluation of next-generation audio-visual speech enhancement and separation systems, including multimodal assistive hearing
and communication technologies. </span></p>
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<span style="font-family: Calibri, sans-serif; font-size: 9pt; color: rgb(0, 0, 0);">The success of the two previous editions of the Challenge (organized as part of IEEE SLT 2022 and IEEE ASRU 2023) demonstrates a consistent trend of system improvement, yet
highlights an enduring intelligibility gap when compared to clean speech. </span>
<span style="font-family: Calibri, sans-serif; font-size: 9pt; color: rgb(13, 13, 13); background-color: rgb(255, 255, 255);">We anticipate that the third edition will further enhance system performance and provide a networking and collaborative platform for
deliberating on the scope, challenges and opportunities in co-designing and evaluating future speech and hearing technologies.</span></p>
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<span style="font-family: Calibri, sans-serif; font-size: 9pt; color: rgb(0, 0, 0);">To register for the challenge please follow the guidelines on the website:</span></p>
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<span style="font-family: Calibri, sans-serif; font-size: 9pt; color: rgb(70, 120, 134);"><a href="https://challenge.cogmhear.org/#/getting-started/register" id="OWA2fb6b6b0-4a0d-49cf-a8b5-24d2a416b684" class="OWAAutoLink" style="text-decoration: none; margin-top: 0px; margin-bottom: 0px; color: rgb(70, 120, 134);">https://challenge.cogmhear.org/#/getting-started/register</a></span><span style="font-family: Calibri, sans-serif; font-size: 9pt; color: rgb(0, 0, 0);"> </span></p>
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<span style="font-family: Calibri, sans-serif; font-size: 9pt; color: rgb(0, 0, 0);">We welcome submissions from participants of the
</span><span style="font-family: Calibri, sans-serif; font-size: 9pt; font-weight: 700; color: rgb(0, 0, 0);">second (AVSEC-2) and third editions (AVSEC-3)</span><span style="font-family: Calibri, sans-serif; font-size: 9pt; color: rgb(0, 0, 0);"> of the Challenge
and also invite submissions on </span><span style="font-family: Calibri, sans-serif; font-size: 9pt; font-weight: 700; color: rgb(0, 0, 0);">related research topics</span><span style="font-family: Calibri, sans-serif; font-size: 9pt; color: rgb(0, 0, 0);">,
including but not limited to the following:</span></p>
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<span style="font-family: Calibri, sans-serif; font-size: 9pt; color: rgb(0, 0, 0);">- Low-latency approaches to audio-visual speech enhancement and separation.</span></p>
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<span style="font-family: Calibri, sans-serif; font-size: 9pt; color: rgb(0, 0, 0);">- Human auditory-inspired models of multi-modal speech perception and enhancement.</span></p>
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<span style="font-family: Calibri, sans-serif; font-size: 9pt; color: rgb(0, 0, 0);">- Energy-efficient audio-visual speech enhancement and separation methods.</span></p>
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<span style="font-family: Calibri, sans-serif; font-size: 9pt; color: rgb(0, 0, 0);">- Machine learning for diverse target listeners and diverse listening scenarios.</span></p>
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<span style="font-family: Calibri, sans-serif; font-size: 9pt; color: rgb(0, 0, 0);">- Audio quality and intelligibility assessment of audio-visual speech enhancement systems.</span></p>
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<span style="font-family: Calibri, sans-serif; font-size: 9pt; color: rgb(0, 0, 0);">- Objective metrics to predict quality and intelligibility from audio-visual stimuli.</span></p>
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<span style="font-family: Calibri, sans-serif; font-size: 9pt; color: rgb(0, 0, 0); background-color: rgb(255, 255, 255);">- Understanding human speech perception in competing speaker scenarios.</span></p>
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<span style="font-family: Calibri, sans-serif; font-size: 9pt; color: rgb(0, 0, 0); background-color: rgb(255, 255, 255);">- Clinical applications and live demonstrators of audio-visual speech enhancement and separation, (e.g. multi-modal hearing assistive
technologies for hearing-impaired listeners; speech-enabled communication aids to support autistic people with speech disorders).</span></p>
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<span style="font-family: Calibri, sans-serif; font-size: 9pt; color: rgb(0, 0, 0);">- Accessibility and human-centric factors in the design and evaluation of innovative multimodal technologies, including multi-modal corpus development, public perceptions,
ethics considerations, standards, societal, economic and political impacts. </span></p>
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<span style="font-family: Calibri, sans-serif; font-size: 9pt; color: rgb(0, 0, 0);">Accepted Workshop papers (both short 2-page and full-length papers of 4-6 pages) will be published in ISCA Proceedings. Authors of selected papers (including winners and runner-ups
of each Challenge Track) will be invited to submit significantly extended papers for consideration in a Special Issue of the IEEE Journal of Selected Topics in Signal Processing (JSTSP) on "Deep Multimodal Speech Enhancement and Separation" - CFP available
below and here: </span><span style="font-family: Calibri, sans-serif; font-size: 9pt; color: rgb(70, 120, 134);"><a href="https://signalprocessingsociety.org/publications-resources/special-issue-deadlines/ieee-jstsp-special-issue-deep-multimodal-speech-enhancement-and-separation" id="OWAa6a14334-5dff-c70f-a3fa-8de2a5c03a78" class="OWAAutoLink" style="text-decoration: none; margin-top: 0px; margin-bottom: 0px; color: rgb(70, 120, 134);">https://signalprocessingsociety.org/publications-resources/special-issue-deadlines/ieee-jstsp-special-issue-deep-multimodal-speech-enhancement-and-separation</a></span><span style="font-family: Calibri, sans-serif; font-size: 9pt; color: rgb(0, 0, 0);"> -
full manuscript submission deadline: 30 Sep 2024)</span></p>
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<span style="font-family: Calibri, sans-serif; font-size: 9pt; color: rgb(0, 0, 0);"><b>CFP: <a href="https://signalprocessingsociety.org/publications-resources/special-issue-deadlines/ieee-jstsp-special-issue-deep-multimodal-speech-enhancement-and-separation" id="OWAf1561746-1063-03f8-5c3a-ab4cd5951fc4" class="OWAAutoLink" data-loopstyle="linkonly" style="text-decoration: none; margin-top: 0px; margin-bottom: 0px; color: rgb(0, 0, 0);">IEEE
Journal of Selected Topics in Signal Processing (JSTSP) Special Issue on: Deep Multimodal Speech Enhancement and Separation</a></b></span></p>
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<span style="font-family: Calibri, sans-serif; font-size: 9pt; color: rgb(0, 0, 0);"><a href="https://signalprocessingsociety.org/publications-resources/special-issue-deadlines/ieee-jstsp-special-issue-deep-multimodal-speech-enhancement-and-separation" id="OWAad37d51b-7c39-8b8b-655c-780dda2dadd7" class="OWAAutoLink" style="text-decoration: none; margin-top: 0px; margin-bottom: 0px; color: rgb(0, 0, 0);">https://signalprocessingsociety.org/publications-resources/special-issue-deadlines/ieee-jstsp-special-issue-deep-multimodal-speech-enhancement-and-separation</a> </span></p>
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<span style="font-family: "Open Sans", sans-serif; font-size: 9pt; font-weight: 700; color: rgb(51, 51, 51);">Manuscript Due: 30 September 2024</span></p>
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<span style="font-family: "Open Sans", sans-serif; font-size: 9pt; color: rgb(51, 51, 51);">Publication Date: May 2025</span></p>
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<span style="font-family: Calibri, sans-serif; font-size: 9pt; font-weight: 700; color: rgb(0, 0, 0);">Scope</span></p>
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<span style="font-family: "Open Sans", sans-serif; font-size: 9pt; color: rgb(51, 51, 51);">Voice is the most commonly used modality by humans to communicate and psychologically blend into society. Recent technological advances have triggered the development
of various voice-related applications in the information and communications technology market. However, noise, reverberation, and interfering speech are detrimental for effective communications between humans and other humans or machines, leading to performance
degradation of associated voice-enabled services. To address the formidable speech-in-noise challenge, a range of speech enhancement (SE) and speech separation (SS) techniques are normally employed as important front-end speech processing units to handle distortions
in input signals in order to provide more intelligible speech for automatic speech recognition (ASR), synthesis and dialogue systems. Emerging advances in artificial intelligence (AI) and machine learning, particularly deep neural networks, have led to remarkable
improvements in SE and SS based solutions. A growing number of researchers have explored various extensions of these methods by utilising a variety of modalities as auxiliary inputs to the main speech processing task to access additional information from heterogeneous
signals. In particular, multi-modal SE and SS systems have been shown to deliver enhanced performance in challenging noisy environments by augmenting the conventional speech modality with complementary information from multi-sensory inputs, such as video,
noise type, signal-to-noise ratio (SNR), bone-conducted speech (vibrations), speaker, text information, electromyography, and electromagnetic midsagittal articulometer (EMMA) data. Various integration schemes, including early and late fusions, cross-attention
mechanisms, and self-supervised learning algorithms, have also been successfully explored.</span></p>
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<span style="font-family: Arial, sans-serif; font-size: 9pt; font-weight: 700; color: rgb(45, 50, 55);">Topics</span></h4>
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<span style="font-family: "Open Sans", sans-serif; font-size: 9pt; color: rgb(51, 51, 51);">This timely special issue aims to collate latest advances in multi-modal SE and SS systems that exploit both conventional and unconventional modalities to further improve
state-of-the-art performance in benchmark problems. We particularly welcome submissions for novel deep neural network based algorithms and architectures, including new feature processing methods for multimodal and cross-modal speech processing. We also encourage
submissions that address practical issues related to multimodal data recording, energy-efficient system design and real-time low-latency solutions, such as for assistive hearing and speech communication applications.</span></p>
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<span style="font-family: "Open Sans", sans-serif; font-size: 9pt; color: rgb(51, 51, 51);">Special Issue research topics of interest relate to open problems needing addressed These include, but are not limited to, the following.</span></p>
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<span style="font-family: "Open Sans", sans-serif; font-size: 9pt; color: rgb(51, 51, 51);">Novel acoustic features and architectures for multi-modal SE (MM-SE) and multi-modal SS (MM-SS) solutions.</span></p>
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<p style="direction: ltr; line-height: 1.38; margin-top: 0pt; margin-bottom: 0pt; background-color: rgb(255, 255, 255);">
<span style="font-family: "Open Sans", sans-serif; font-size: 9pt; color: rgb(51, 51, 51);">Self-supervised and unsupervised learning techniques for MM-SE and MM-SS systems.</span></p>
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<span style="font-family: "Open Sans", sans-serif; font-size: 9pt; color: rgb(51, 51, 51);">Adversarial learning for MM-SE and MM-SS.</span></p>
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<p style="direction: ltr; line-height: 1.38; margin-top: 0pt; margin-bottom: 0pt; background-color: rgb(255, 255, 255);">
<span style="font-family: "Open Sans", sans-serif; font-size: 9pt; color: rgb(51, 51, 51);">Large language model-based Generative approaches for MM-SE and MM-SS</span></p>
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<p style="direction: ltr; line-height: 1.38; margin-top: 0pt; margin-bottom: 0pt; background-color: rgb(255, 255, 255);">
<span style="font-family: "Open Sans", sans-serif; font-size: 9pt; color: rgb(51, 51, 51);">Low-delay, low-power, low-complexity MM-SE and MM-SS models</span></p>
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<span style="font-family: "Open Sans", sans-serif; font-size: 9pt; color: rgb(51, 51, 51);">Integration of multiple data acquisition devices for multimodal learning and novel learning algorithms robust to imperfect data.</span></p>
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<span style="font-family: "Open Sans", sans-serif; font-size: 9pt; color: rgb(51, 51, 51);">Few-shot/zero-shot learning and adaptation algorithms for MM-SE and MM-SS systems with a small amount of training and adaptation data.</span></p>
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<span style="font-family: "Open Sans", sans-serif; font-size: 9pt; color: rgb(51, 51, 51);">Approaches that effectively reduce model size and inference cost without reducing the speech quality and intelligibility of processed signals.</span></p>
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<span style="font-family: "Open Sans", sans-serif; font-size: 9pt; color: rgb(51, 51, 51);">Novel objective functions including psychoacoustics and perceptually motivated loss functions for MM-SE and MM-SS</span></p>
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<span style="font-family: "Open Sans", sans-serif; font-size: 9pt; color: rgb(51, 51, 51);">Holistic evaluation metrics for MM-SE and MM-SS systems.</span></p>
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<span style="font-family: "Open Sans", sans-serif; font-size: 9pt; color: rgb(51, 51, 51);">Real-world applications and use-cases of MM-SE and MM-SS, including human-human and human-machine communications</span></p>
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<span style="font-family: "Open Sans", sans-serif; font-size: 9pt; color: rgb(51, 51, 51);">Challenges and solutions in the integration of MM-SE and MM-SS into existing systems</span></p>
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<span style="font-family: "Open Sans", sans-serif; font-size: 9pt; color: rgb(51, 51, 51);">We encourage submissions that not only propose novel approaches but also substantiate the findings with rigorous evaluations, including real-world datasets. Studies
that provide insights into the challenges involved and the impact of MM-SE and MM-SS on end-users are particularly welcome.</span></p>
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<span style="font-family: Arial, sans-serif; font-size: 9pt; font-weight: 700; color: rgb(45, 50, 55);">Submission Guidelines</span></h4>
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<span style="font-family: "Open Sans", sans-serif; font-size: 9pt; color: rgb(51, 51, 51);">Manuscripts should be original and should not have been previously published or currently under consideration for publication elsewhere. All submissions will be peer-reviewed
according to the IEEE Signal Processing Society review process. Authors should prepare their manuscripts according to the Instructions for Authors available from the Signal Processing Society website.</span></p>
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<span style="font-family: "Open Sans", sans-serif; font-size: 9pt; color: rgb(51, 51, 51);">Follow the instructions given on the IEEE
</span><span style="font-family: "Open Sans", sans-serif; font-size: 9pt; color: rgb(13, 103, 151);"><a href="https://signalprocessingsociety.org/publications-resources/ieee-journal-selected-topics-signal-processing" id="OWA5f97d1d7-af46-df20-6f1b-b4338ca8238c" class="OWAAutoLink" data-loopstyle="linkonly" style="text-decoration: none; margin-top: 0px; margin-bottom: 0px; color: rgb(13, 103, 151);">JSTSP
webpage</a></span><span style="font-family: "Open Sans", sans-serif; font-size: 9pt; color: rgb(51, 51, 51);">: and
</span><span style="font-family: "Open Sans", sans-serif; font-size: 9pt; color: rgb(13, 103, 151);"><a href="https://mc.manuscriptcentral.com/jstsp-ieee" id="OWA3d386ecb-b41b-1bdf-07e6-26f5c1e825e5" class="OWAAutoLink" data-loopstyle="linkonly" style="text-decoration: none; margin-top: 0px; margin-bottom: 0px; color: rgb(13, 103, 151);">submit
manuscripts</a></span><span style="font-family: "Open Sans", sans-serif; font-size: 9pt; color: rgb(51, 51, 51);">.</span></p>
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<span style="font-family: Arial, sans-serif; font-size: 9pt; font-weight: 700; color: rgb(45, 50, 55);">Important Dates</span></h3>
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<span style="font-family: Calibri, sans-serif; font-size: 9pt; color: rgb(0, 0, 0);">Manuscript Submission Deadline: 30 September 2024</span></p>
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<span style="font-family: Calibri, sans-serif; font-size: 9pt; color: rgb(0, 0, 0);">First Review Due: 15 December 2024</span></p>
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<span style="font-family: Calibri, sans-serif; font-size: 9pt; color: rgb(0, 0, 0);">Revised Manuscript Due: 15 January 2024</span></p>
<p style="direction: ltr; line-height: 1.38; margin-top: 0pt; margin-bottom: 0pt; background-color: rgb(255, 255, 255);">
<span style="font-family: Calibri, sans-serif; font-size: 9pt; color: rgb(0, 0, 0);">Second Review Due: 15 February 2024</span></p>
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<span style="font-family: Calibri, sans-serif; font-size: 9pt; color: rgb(0, 0, 0);">Final Decision: 28 February 2025</span></p>
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<span style="font-family: "Open Sans", sans-serif; font-size: 9pt; font-weight: 700; color: rgb(51, 51, 51);">Guest Editors</span></p>
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<span style="font-family: "Open Sans", sans-serif; font-size: 9pt; color: rgb(51, 51, 51);"></span><span style="font-family: Calibri, sans-serif; font-size: 9pt; color: rgb(0, 0, 0);">For further information, please contact the guest editors at: </span></p>
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<span style="font-family: Calibri, sans-serif; font-size: 9pt; color: rgb(70, 120, 134);">Amir Hussain</span><span style="font-family: Calibri, sans-serif; font-size: 9pt; color: rgb(0, 0, 0);">, Edinburgh Napier University, UK (Lead GE)</span></p>
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<span style="font-family: Calibri, sans-serif; font-size: 9pt; color: rgb(70, 120, 134);">Yu Tsao</span><span style="font-family: Calibri, sans-serif; font-size: 9pt; color: rgb(0, 0, 0);">, Academia Sinica, Taiwan (co-Lead GE)</span></p>
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<span style="font-family: Calibri, sans-serif; font-size: 9pt; color: rgb(70, 120, 134);">John H.L. Hansen</span><span style="font-family: Calibri, sans-serif; font-size: 9pt; color: rgb(0, 0, 0);">, University of Texas at Dallas, USA</span></p>
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<span style="font-family: Calibri, sans-serif; font-size: 9pt; color: rgb(70, 120, 134);">Naomi Harte</span><span style="font-family: Calibri, sans-serif; font-size: 9pt; color: rgb(0, 0, 0);">, Trinity College Dublin, Ireland</span></p>
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<span style="font-family: Calibri, sans-serif; font-size: 9pt; color: rgb(70, 120, 134);">Shinji Watanabe</span><span style="font-family: Calibri, sans-serif; font-size: 9pt; color: rgb(0, 0, 0);">, Carnegie Mellon University, USA</span></p>
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<span style="font-family: Calibri, sans-serif; font-size: 9pt; color: rgb(70, 120, 134);">Isabel Trancoso</span><span style="font-family: Calibri, sans-serif; font-size: 9pt; color: rgb(0, 0, 0);">, Instituto Superior Técnico, IST, Univ. Lisbon, Portugal</span></p>
<div style="font-family:Calibri,sans-serif; font-size:9pt"><span style="color: rgb(70, 120, 134);">Shixiong Zhang</span><span style="color: rgb(0, 0, 0);">, Tencent AI Lab, USA</span></div>
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<span style="font-family:Calibri, sans-serif;font-size:9pt">We look forward to your submissions. </span></p>
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<span style="font-family:Calibri, sans-serif;font-size:9pt">Many thanks in advance, </span></p>
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<span style="font-family:Aptos, Aptos_EmbeddedFont, Aptos_MSFontService, Calibri, Helvetica, sans-serif;font-size:9pt"><br>
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<span style="font-family:Calibri, sans-serif;font-size:9pt">Prof Amir Hussain </span></p>
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<span style="font-family:Calibri, sans-serif;font-size:9pt">Edinburgh Napier University, Scotland, UK </span></p>
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<span style="font-family:Calibri, sans-serif;font-size:9pt">E-mail: A.Hussain@napier.ac.uk </span></p>
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<span style="font-family:Calibri, sans-serif;font-size:9pt"><a rel="noreferrer noopener" href="https://www.napier.ac.uk/people/amir-hussain">https://www.napier.ac.uk/people/amir-hussain</a><br>
</span></p>
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<span style="font-family:Calibri, sans-serif;font-size:9pt"><a href="http://cogmhear.org/" id="OWA9290e231-5a59-b159-6a7d-0852f92992ac" class="OWAAutoLink" data-loopstyle="linkonly" style="text-decoration:none;margin-top:0px;margin-bottom:0px">http://cogmhear.org</a> </span></p>
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