IRES Track I: US-Mexico Collaboration on Multimodal Detection of Objectionable Content in Online Videos in Spanish and English

儿童娱乐的主要形式来自电影、电子游戏和在线多媒体内容。这些大众传媒传播来源的内容有可能对行为产生负面影响，尤其是对年轻观众。IRES团队将设计、实施和评估新的多模式技术，以检测对观众产生负面影响的内容的存在，同时在多文化、多语言的国际环境中培训研究生和本科生的研究和专业技能。该项目利用了休斯顿大学教师与墨西哥国立研究所Astrofísica， Óptica y Electrónica （INAOE）之间的长期合作。IRES学生将接受多语种语言处理、图像/视频分析和多模态数据深度学习方法的培训和指导。这个IRES项目的目标是通过培训一批未来的计算机科学专业人员（称为“IRES学者”）来促进美国国家STEM劳动力的增长，使他们能够在多学科和多元文化的环境中茁壮成长，并使他们能够获得从事人工智能研究和开发所需的知识和技能。通过该项目，IRES学者将接触到计算机视觉，自然语言处理和深度学习方面的最新研究。他们将设计、实施和评估新的算法和系统，通过清晰、准确地描述潜在的问题在线内容，为年轻观众提供更安全的在线空间。该项目采用基于证据的指导，这将支持项目的可持续性。这个IRES项目的目标是1)在多语言和多领域设置中推进多模态内容自动分析研究领域的最新技术；2)培养具有跨学科和多元文化研究技能的学生加入多元化的全球STEM/知识劳动力；3)提高来自STEM中代表性不足群体的研究生和本科生的热情，研究技能和专业技能，否则他们可能没有国际专业发展机会；4)让学生沉浸在以西班牙语为母语的社区中，以支持他们参与真正的跨文化和多语言培训体验。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

A major form of entertainment for children comes from movies, video games, and online multi-media content. Content from these mass media communications sources has the potential to negatively affect behavior, especially of young viewers. The IRES team will design, implement, and evaluate new multi-modal technologies to detect the presence of content that has been linked to negative effects on viewers while training graduate and undergraduate student in research and professional skills in a multi-cultural, multilingual international environment. The project leverages a long-standing collaboration between faculty at the University of Houston and the Instituto Nacional de Astrofísica, Óptica y Electrónica (INAOE) of Mexico. IRES students will be trained and mentored on multilingual methods of language processing, image/video analysis, and deep learning for multimodal data. The goal of this IRES project is to contribute to the growth of the U.S. national STEM workforce by training a cohort of future computer science professionals (referred to as “IRES Scholars”) to thrive in a multidisciplinary and multicultural environment and enabling them to acquire the necessary knowledge and skills to pursue artificial intelligence research and development. Through this project, IRES Scholars will be exposed to state-of-the-art research in computer vision, natural language processing, and deep learning. They will design, implement, and evaluate new algorithms and systems that will contribute to the crucial goal of providing safer online spaces for young viewers through clear and accurate descriptions of potentially problematic online content. The project employs evidence-based mentoring that will support program sustainability.The objectives of this IRES project are to 1) advance the state-of-the-art in the research field of automated analysis of multimodal content in multilingual and multidomain settings; 2) prepare students with cross-disciplinary and multicultural research skills to join a diverse and global STEM/knowledge workforce; 3) increase enthusiasm, research skills, and professional skills of graduate and undergraduate students from underrepresented population groups in STEM who otherwise might not have an international opportunity for professional development; and 4) immerse students in a community of native Spanish speakers to support engagement in an authentic cross-cultural and multilingual training experience.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.