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MMLLRL 2022 : WORKSHOP ON MULTIMODAL MACHINE LEARNING IN LOW-RESOURCE LANGUAGES

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Link: https://sites.google.com/view/mmlow-icon2022/home?authuser=0
 
When Dec 15, 2022 - Dec 15, 2022
Where IIIT Delhi, India
Submission Deadline Oct 30, 2022
Notification Due Nov 15, 2022
Final Version Due Nov 1, 2022
Categories    NLP   artificial intelligence
 

Call For Papers



No suele recibir correos electrónicos de corpora@list.elra.info. Por qué esto es importante


Second Call for papers

WORKSHOP ON MULTIMODAL MACHINE LEARNING IN LOW-RESOURCE LANGUAGES at ICON 2022

Link: https://sites.google.com/view/mmlow-icon2022/home?authuser=0


In recent years, the exploitation of the potential of big data has resulted in significant advancements in a variety of Computer Vision and Natural Language Processing applications. However, the majority of tasks addressed thus far have been primarily visual in nature due to the unbalanced availability of labelled samples across modalities (e.g., there are numerous large labelled datasets for images but few for audio or IMU-based classification), resulting in a large performance gap when algorithms are trained separately. With its origins in audio-visual speech recognition and, more recently, in language and vision projects such as image and video captioning, multimodal machine learning is a thriving multidisciplinary research field that addresses several of artificial intelligence's (AI) original goals by integrating and modelling multiple communicative modalities, including linguistic, acoustic, and visual messages. Due to the variability of the data and the frequently observed dependency between modalities, this study subject presents some particular problems for machine learning researchers. Because the majority of this hateful content is in regional languages, they easily slip past online surveillance algorithms that are designed to target articles written in resource-rich languages like English. As a result, low-resource regional languages in Asia, Africa, Europe, and South America face a shortage of tools, benchmark datasets, and machine learning approaches.




This workshop aims to bring together members of the machine learning and multimodal data fusion fields in regional languages. We anticipate contributions that hate speech and emotional analysis in multimodality include video, audio, text, drawings, and synthetic material in regional language. This workshop's objective is to advance scientific study in the broad field of multimodal interaction, techniques, and systems, emphasising important trends and difficulties in regional languages, with a goal of developing a roadmap for future research and commercial success.








We invite submissions on topics that include, but are not limited to, the following:




Multimodal Sentiment Analysis in regional languages



Hate content video detection in regional languages



Trolling and Offensive post detection in Memes



Multimodal data fusion and data representation for hate speech detection in regional language



Multimodal hate speech benchmark datasets and evaluations in regional languages



Multimodal fake news in regional languages



Data collection and annotation methodologies for safer social media in low-resourced languages



Content moderation strategies in regional languages



Cybersecurity and social media in regional languages



Important Dates:


Paper Submission Deadline:
Oct 30, 2022


Paper Acceptance Notification:
Nov 15, 2022


Camera-ready Submission Deadline:
Dec 01, 2022


Workshop:
Dec 15, 2022






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