Dear Colleagues,

We are organizing a Special Issue at the IEEE Transactions on Multimedia:
'Pre-trained Models for Multi-Modality Understanding'

Submission deadline: January 15, 2023
First Review: April 1, 2023
Revisions due: June 1, 2023
Second Review: August 15, 2023
Final Manuscripts: September 15, 2023
Publication date: September 30, 2023

For more details please visit our CFP website at:
https://signalprocessingsociety.org/sites/default/files/uploads/special_issues_deadlines/TMM_SI_pre_trained.pdf
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Best regards,
Zakia Hammal

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Call for Papers]
Advanced Robotics Special Issue on
Multimodal Processing and Robotics for Dialogue Systems
Co-Editors:
Prof. David Traum (University of Southern California, USA)
Prof. Gabriel Skantze (KTH Royal Institute of Technology, Sweden)
Prof. Hiromitsu Nishizaki (University of Yamanashi, Japan)
Prof. Ryuichiro Higashinaka (Nagoya University, Japan)
Dr. Takashi Minato (RIKEN/ATR, Japan)
Prof. Takayuki Nagai (Osaka University, Japan)
               
Publication in Vol. 37, Issue 21 (Nov 2023)
SUBMISSION DEADLINE: 31 Jan  2023

In recent years, as seen in smart speakers such as Google Home and Amazon Alexa, there has been remarkable progress in spoken dialogue systems technology to converse with users with human-like utterances. In the future, such dialogue systems are expected to support our daily activities in various ways. However, dialogue in daily activities is more complex than that with smart speakers; even with current spoken dialogue technology, it is still difficult to maintain a successful dialogue in various situations. For example, in customer service through dialogue, it is necessary for operators to respond appropriately to the different ways of speaking and requests of various customers. In such cases, we humans can switch the speaking manner depending on the type of customer, and we can successfully perform the dialogue by not only using our voice but also our gaze and facial expressions.
This type of human-like interaction is far from possible with the existing spoken dialogue systems. Humanoid robots have the possibility to realize such an interaction, because they can recognize not only the user's voice but also facial expressions and gestures using various sensors, and can express themselves in various ways such as gestures and facial expressions using their bodies. Their many means of expressions have the potential to successfully continue dialogue in a manner different from conventional dialogue systems.
The combination of such robots and dialogue systems can greatly expand the possibilities of dialogue systems, while at the same time, providing a variety of new challenges. Various research and development efforts are currently underway to address these new challenges, including 'dialogue robot competition' at IROS2022.
In this special issue, we invite a wide range of papers on multimodal dialogue systems and dialogue robots, their applications, and fundamental research. Prospective contributed papers are invited to cover, but are not limited to, the following topics on multimodal dialogue systems and robots:
 
*Spoken dialogue processing
*Multimodal processing
*Speech recognition
*Text-to-speech
*Emotion recognition
*Motion generation
*Facial expression generation
*System architecture
*Natural language processing
*Knowledge representation
*Benchmarking
*Evaluation method
*Ethics
*Dialogue systems and robots for competition
Submission:
The full-length manuscript (either PDF file or MS word file) should be sent by 31st Jan 2023 to the office of Advanced Robotics, the Robotics Society of Japan through the on-line submission system of the journal (https://www.rsj.or.jp/AR/submission). Sample manuscript templates and detailed instructions for authors are available at the website of the journal.
Note that word count includes references. Captions and author bios are not included.
For special issues, longer papers can be accepted if the editors approve.
Please contact the editors before the submission if your manuscript exceeds the word limit.

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ACM Transactions on Multimedia Computing, Communications, and Applications
Special Issue on Realistic Synthetic Data: Generation, Learning, Evaluation
Impact Factor 4.094
https://mc.manuscriptcentral.com/tomm
Submission deadline: 31 March 2023


*** CALL FOR PAPERS ***

[Guest Editors]
Bogdan Ionescu, Universitatea Politehnica din Bucuresti, România
Ioannis Patras, Queen Mary University of London, UK
Henning Muller, University of Applied Sciences Western Switzerland, Switzerland
Alberto Del Bimbo, Università degli Studi di Firenze, Italy

[Scope]
In the current context of Machine Learning (ML) and Deep Learning
(DL), data and especially high-quality data are central for ensuring
proper training of the networks. It is well known that DL models
require an important quantity of annotated data to be able to reach
their full potential. Annotating content for models is traditionally
made by human experts or at least by typical users, e.g., via
crowdsourcing. This is a tedious task that is time consuming and
expensive -- massive resources are required, content has to be curated
and so on. Moreover, there are specific domains where data
confidentiality makes this process even more challenging, e.g., in the
medical domain where patient data cannot be made publicly available,
easily.

With the advancement of neural generative models such as Generative
Adversarial Networks (GAN), or, recently diffusion models, a promising
way of solving or alleviating such problems that are associated with
the need for domain specific annotated data is to go toward realistic
synthetic data generation. These data are generated by learning
specific characteristics of different classes of target data. The
advantage is that these networks would allow for infinite variations
within those classes while producing realistic outcomes, typically
hard to distinguish from the real data. These data have no proprietary
or confidentiality restrictions and seem a viable solution to generate
new datasets or augment existing ones. Existing results show very
promising results for signal generation, images etc.

Nevertheless, there are some limitations that need to be overcome so
as to advance the field. For instance, how can one control/manipulate
the latent codes of GANs, or the diffusion process, so as to produce
in the output the desired classes and the desired variations like real
data? In many cases, results are not of high quality and selection
should be made by the user, which is like manual annotation. Bias may
intervene in the generation process due to the bias in the input
dataset. Are the networks trustworthy? Is the generated content
violating data privacy? In some cases one can predict based on a
generated image the actual data source used for training the network.
Would it be possible to train the networks to produce new classes and
learn causality of the data? How do we objectively assess the quality
of the generated data? These are just a few open research questions.

[Topics]
In this context, the special issue is seeking innovative algorithms
and approaches addressing the following topics (but is not limited
to):
- Synthetic data for various modalities, e.g., signals, images,
volumes, audio, etc.
- Controllable generation for learning from synthetic data.
- Transfer learning and generalization of models.
- Causality in data generation.
- Addressing bias, limitations, and trustworthiness in data generation.
- Evaluation measures/protocols and benchmarks to assess quality of
synthetic content.
- Open synthetic datasets and software tools.
- Ethical aspects of synthetic data.

[Important Dates]
- Submission deadline: 31 March 2023
- First-round review decisions: 30 June 2023
- Deadline for revised submissions: 31 July 2023
- Notification of final decisions: 30 September 2023
- Tentative publication: December 2023

[Submission Information]
Prospective authors are invited to submit their manuscripts
electronically through the ACM TOMM online submission system (see
https://mc.manuscriptcentral.com/tomm) while adhering strictly to the
journal guidelines (see https://tomm.acm.org/authors.cfm). For the
article type, please select the Special Issue denoted SI: Realistic
Synthetic Data: Generation, Learning, Evaluation.

Submitted manuscripts should not have been published previously, nor
be under consideration for publication elsewhere. If the submission is
an extended work of a previously published conference paper, please
include the original work and a cover letter describing the new
content and results that were added. According to ACM TOMM publication
policy, previously published conference papers can be eligible for
publication provided that at least 40% new material is included in the
journal version.

[Contact]
For questions and further information, please contact Bogdan Ionescu /
bogdan.ionescu@upb.ro.

[Acknowledgement]
The Special Issue is endorsed by the AI4Media 'A Centre of Excellence
delivering next generation AI Research and Training at the service of
Media, Society and Democracy' H2020 ICT-48-2020 project
https://www.ai4media.eu/.

On behalf of the Guest Editors,
Bogdan Ionescu
https://www.aimultimedialab.ro/

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Dear Speech Prosody SIG members,

Rajiv Rao is inviting submissions for a special issue on Prosody and Immigration in Languages, a MDPI Journal.  Please see

https://www.mdpi.com/journal/languages/special_issues/DTB64LM303 for details.

Research on minority immigrant languages has gained significant traction in the last decade-plus, primarily due to a significant body of research on heritage languages (e.g., Montrul, 2015; Polinsky, 2018; Polinsky & Montrul, 2021; among many others). Developments in the phonetics and phonology of heritage languages have lagged behind those in other linguistic areas, but recent years have seen significant growth in work on sound systems as well (see, e.g., Chang, 2021; Rao, 2016, in press), especially in North America, thanks in large part to research on Spanish in the US (for an overview, see Rao, 2019) and studies based on the Heritage Language Variation and Change Corpus in Toronto (Nagy, 2011). However, within the fields of heritage (and, in general, minority immigrant language) phonetics and phonology, prosody remains relatively understudied, and within the realm of immigrant language prosody, we still know very little about issues such as cross-generational change, longitudinal outcomes, child versus adolescent versus adult data, older first-generation immigrants who have resided in the host country for multiple decades versus monolingual homeland speakers, the role of source input varieties, the influence of a wide range of social (level of education, age, gender, rural versus urban settings, etc.) and affective (e.g., attitudes, emotions, motivation) variables, speech rhythm, intonation across a variety of pragmatic contexts, variation in lexical tone, speakers of such languages outside of North America, and the effects of minority language prosody on local majority varieties (by no means is this an exhaustive list).

The goal of this Special Issue is to fill existing holes in the literature on prosody by addressing the topics listed above (among other possibilities), while highlighting the need for increased comparisons between first-generation immigrants and homeland speakers, as well as a wider range of coverage of languages and geographies in general (e.g., Calhoun, 2015 versus Calhoun et al., in press for data based in Oceania). Finally, this special issue complements other ones hosted by Languages:
https://www.mdpi.com/journal/languages/special_issues/Immigrant_Refugee_Languagees
https://www.mdpi.com/journal/languages/special_issues/multilingualism_migrant

Given that prosody is a key component of human communication (e.g., Gussenhoven & Chen, 2020) and that language and cultural contact caused by international movement are pervasive in many regions of the world, learning more about the interaction of these two concepts is important, not only to expand on the recent growth in heritage language sound systems, but also to gain a deeper understanding of the underpinnings of prosodic variation (for a recent contribution to this area, see Armstrong et al., 2022).

We request that, prior to submitting a manuscript, interested authors initially submit a proposed title and an abstract of 400–600 words summarizing their intended contribution. Please send it to the Guest Editor (Rajiv Rao; rgrao@wisc.edu) or to the Languages Editorial Office (languages@mdpi.com). Abstracts will be reviewed by the Guest Editor for the purposes of ensuring proper fit within the scope of the Special Issue. Full manuscripts will undergo double-blind peer-review.

Tentative completion schedule:

• Abstract submission deadline: May 15, 2023
• Notification of abstract acceptance: May 31, 2023
• Full manuscript deadline: August 31, 2023

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Submissions are invited for a new journal in the area of connected speech. To submit articles please go to https://journal.equinoxpub.com/JCS/about/submissions

The aim of the Journal of Connected Speech is to provide a platform for the study of connected speech in both its formal and functional aspects (from prosody to discourse analysis). The journal explores issues linked to transcription systems, instrumentation, and data collection methodology, as well as models within broadly functional, cognitive, and psycholinguistic approaches.

The journal launches in 2024. See https://journal.equinoxpub.com/index.php/JCS/index

If you have any queries, please contact me at m.j.ball@bangor.ac.uk

Martin J. Ball, DLitt, PhD, HonFRCSLT, FLSW

Athro er Anrhydedd,

Ysgol Iaith, Diwylliant a'r Celfyddydau,

Prifysgol Bangor, Cymru.

(Hefyd Athro Gwadd, Prifysgol Glynd?r Wrecsam)

Honorary Professor,

School of Arts, Culture and Language,

Bangor University, Wales.

(Also Visiting Professor, Wrexham Glynd?r University)

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