Multimodal Grounding for Language Processing

This survey discusses how recent developments in multimodal processing facilitate conceptual grounding of language. We categorize the information flow in multimodal processing with respect to cognitive models of human information processing and analyze different methods for combining multimodal representations. Based on this methodological inventory, we discuss the benefit of multimodal grounding for a variety of language processing tasks and the challenges that arise. We particularly focus on multimodal grounding of verbs which play a crucial role for the compositional power of language.Comment: The paper has been published in the Proceedings of the 27 Conference of Computational Linguistics. Please refer to this version for citations: https://www.aclweb.org/anthology/papers/C/C18/C18-1197

Image mining: trends and developments

[Abstract]: Advances in image acquisition and storage technology have led to tremendous growth in very large and detailed image databases. These images, if analyzed, can reveal useful information to the human users. Image mining deals with the extraction of implicit knowledge, image data relationship, or other patterns not explicitly stored in the images. Image mining is more than just an extension of data mining to image domain. It is an interdisciplinary endeavor that draws upon expertise in computer vision, image processing, image retrieval, data mining, machine learning, database, and artificial intelligence. In this paper, we will examine the research issues in image mining, current developments in image mining, particularly, image mining frameworks, state-of-the-art techniques and systems. We will also identify some future research directions for image mining

Media literacy at all levels: making the humanities more inclusive

The decline of the humanities, combined with the arrival of students focused on science, technology, engineering, and mathematics (STEM), represent an opportunity for the development of innovative approaches to teaching languages and literatures. Expanding the instructional focus from traditional humanities students, who are naturally more text-focused, to address the needs of more application-oriented STEM learners ensures that language instructors prepare all students to become analytical and critical consumers and producers of digital media. Training students to question motives both in their own and authentic media messages and to justify their own interpretations results in more sophisticated second language (L2) communication. Even where institutional structures impede comprehensive curriculum reform, individual instructors can integrate media literacy training into their own classes. Tis article demonstrates ways of reaching and retaining larger numbers of students at all levels—if necessary, one course at a time.Published versio

Image mining: issues, frameworks and techniques

[Abstract]: Advances in image acquisition and storage technology have led to tremendous growth in significantly large and detailed image databases. These images, if analyzed, can reveal useful information to the human users. Image mining deals with the extraction of implicit knowledge, image data relationship, or other patterns not explicitly stored in the images. Image mining is more than just an extension of data mining to image domain. It is an interdisciplinary endeavor that draws upon expertise in computer vision, image processing, image retrieval, data mining, machine learning, database, and artificial intelligence. Despite the development of many applications and algorithms in the individual research fields cited above, research in image mining is still in its infancy. In this paper, we will examine the research issues in image mining, current developments in image mining, particularly, image mining frameworks, state-of-the-art techniques and systems. We will also identify some future research directions for image mining at the end of this paper

Referential precedents in spoken language comprehension: a review and meta-analysis

Listeners’ interpretations of referring expressions are influenced by referential precedents—temporary conventions established in a discourse that associate linguistic expressions with referents. A number of psycholinguistic studies have investigated how much precedent effects depend on beliefs about the speaker’s perspective versus more egocentric, domain-general processes. We review and provide a meta-analysis of visual-world eyetracking studies of precedent use, focusing on three principal effects: (1) a same speaker advantage for maintained precedents; (2) a different speaker advantage for broken precedents; and (3) an overall main effect of precedents. Despite inconsistent claims in the literature, our combined analysis reveals surprisingly consistent evidence supporting the existence of all three effects, but with different temporal profiles. These findings carry important implications for existing theoretical explanations of precedent use, and challenge explanations based solely on the use of information about speakers’ perspectives

Non\u2011syndromic isolated dominant optic atrophy caused by the p.R468C mutation in the AFG3 like matrix AAA peptidase subunit 2 gene

Autosomal dominant optic atrophy (DOA) is the most frequent form of hereditary optic atrophy, a disease presenting with considerable inter- and intra-familial clinical variability. Although a number of mutations in different genes are now known to cause DOA, many cases remain undiagnosed. In an attempt to identify the underlying genetic defect, whole exome sequencing was performed in a 19-year-old male that had been affected by isolated DOA since childhood. The exome sequencing revealed a pathogenic mutation (p.R468C, c.1402C>T) in the AFG3 like matrix AAA peptidase subunit 2 (AFG3L2) gene, a gene known to be associated with spinocerebellar ataxia. The patient did not show any signs other than DOA. Thus, the result demonstrates the possibility that mutations in the AFG3L2 gene may be a cause of isolated autosomal DOA