Contextually self-organized maps of Chinese words

This is a technical report on the implementation of contextual SOMs of Chinese words. Several new developments are introduced. It seems that when the words are ordered on the SOM topologically, the order is not only determined by the word classes, but also the roles of the words as sentence constituents are reflected in their position on the SOM

Contextually self-organized maps of Chinese words : Part 2

In this second publication on the contextual SOMs of Chinese words, a new effect is reported. The SOM was trained by the complete MCRC corpus used in the previous publication. When its hit diagrams were formed using subsets of words of a certain word class with different word frequencies, the hit distribution was found to be a function of this frequency. An explanation of this effect might be that the usage of the words changes with time, and frequent use accelerates this transformation. Therefore, in planning new experiments on the contextually self-organizing word maps, one should be aware of this effect and take it into account in the selection of words to represent the word classes

Transnational Activism in Support of National Protest: Questions of Identity and Organization

This article considers the question of whether transnational activism supporting national protest attains a cohesive collective identity on social media whilst organizationally remaining localized. It examines a corpus of social media data collected in the course of two months of rolling protests in 2013 against the largest proposed open-cast gold mine at Roşia Montană, Romania, which echoed among Romanian expatriates. A network text analysis of the data supplemented with interview findings revealed concerns with protest logistics as common across the transnational networks of protest localities on both Facebook and Twitter, a finding that testified to the coordinated character of the protests. On the other hand, collective identity emerged as the fruit of attempts to surmount localized protest experiences of geographically disparate but civically-minded social media users

Symbol Emergence in Robotics: A Survey

Humans can learn the use of language through physical interaction with their environment and semiotic communication with other people. It is very important to obtain a computational understanding of how humans can form a symbol system and obtain semiotic skills through their autonomous mental development. Recently, many studies have been conducted on the construction of robotic systems and machine-learning methods that can learn the use of language through embodied multimodal interaction with their environment and other systems. Understanding human social interactions and developing a robot that can smoothly communicate with human users in the long term, requires an understanding of the dynamics of symbol systems and is crucially important. The embodied cognition and social interaction of participants gradually change a symbol system in a constructive manner. In this paper, we introduce a field of research called symbol emergence in robotics (SER). SER is a constructive approach towards an emergent symbol system. The emergent symbol system is socially self-organized through both semiotic communications and physical interactions with autonomous cognitive developmental agents, i.e., humans and developmental robots. Specifically, we describe some state-of-art research topics concerning SER, e.g., multimodal categorization, word discovery, and a double articulation analysis, that enable a robot to obtain words and their embodied meanings from raw sensory--motor information, including visual information, haptic information, auditory information, and acoustic speech signals, in a totally unsupervised manner. Finally, we suggest future directions of research in SER.Comment: submitted to Advanced Robotic

Papers on predicative constructions : Proceedings of the workshop on secundary predication, October 16-17, 2000, Berlin

This volume presents a collection of papers touching on various issues concerning the syntax and semantics of predicative constructions. A hot topic in the study of predicative copula constructions, with direct implications for the treatment of he (how many he's do we need?), and wider implications for the theories of predication, event-based semantics and aspect, is the nature and source of the situation argument. Closer examination of copula-less predications is becoming increasingly relevant to all these issues, as is clearly illustrated by the present collection

Speaker Normalization Using Cortical Strip Maps: A Neural Model for Steady State vowel Categorization

Auditory signals of speech are speaker-dependent, but representations of language meaning are speaker-independent. The transformation from speaker-dependent to speaker-independent language representations enables speech to be learned and understood from different speakers. A neural model is presented that performs speaker normalization to generate a pitch-independent representation of speech sounds, while also preserving information about speaker identity. This speaker-invariant representation is categorized into unitized speech items, which input to sequential working memories whose distributed patterns can be categorized, or chunked, into syllable and word representations. The proposed model fits into an emerging model of auditory streaming and speech categorization. The auditory streaming and speaker normalization parts of the model both use multiple strip representations and asymmetric competitive circuits, thereby suggesting that these two circuits arose from similar neural designs. The normalized speech items are rapidly categorized and stably remembered by Adaptive Resonance Theory circuits. Simulations use synthesized steady-state vowels from the Peterson and Barney [J. Acoust. Soc. Am. 24, 175-184 (1952)] vowel database and achieve accuracy rates similar to those achieved by human listeners. These results are compared to behavioral data and other speaker normalization models.National Science Foundation (SBE-0354378); Office of Naval Research (N00014-01-1-0624

A Proposed Framework Based on Literature Review of Online Contextual Mental Health Services to Enhance Wellbeing and Address Psychopathology During COVID-19

Coronavirus disease (COVID-19) became a pandemic and is causing unprecedented biopsychosocial, spiritual and economic issues across the world while mostly affecting unprivileged populations. Turkey has gradually implemented new regulations, which slowly affected the entire country and increased the need for mental health services disproportionally. We conducted a comprehensive literature review on mental health in Turkey during COVID-19. There was no well-grounded peer-reviewed manuscripts or projects utilized a framework. Therefore, we wrote this manuscript to provide a conceptual framework grounded in ecological systems theory, acceptance and commitment therapy, and community-based participatory action research to introduce contextually evidence-based online mental health services: hotline, psychiatric interview, counseling, and Read-Reflect-Share group bibliotherapy. The framework aims to (1) address biopsychosocial spiritual and economic issues, (2) enhance wellbeing, and (3) empower the mental health profession in research and practice. Our preliminary findings and clinical experience indicated that the proposed framework and interventions derived from the framework enhanced wellbeing and decreased psychopathological symptoms in experimental group compared to control groups. Based on the preliminary analysis, most of the online, phone based, or face-to-face mental health services introduced in this manuscript were highly recommended by the participants to be provided to general public during and after COVID-19. Mental health professionals and authorities can use the proposed framework and interventions to develop interventions and research in order to alleviate pandemic-based biopsychosocial spiritual and economic issues and enhance wellbeing

Discovering the structure and organization of a free Cantonese emotion-label word association graph to understand mental lexicons of emotions

Emotions are not necessarily universal across different languages and cultures. Mental lexicons of emotions depend strongly on contextual factors, such as language and culture. The Chinese language has unique linguistic properties that are different from other languages. As a main variant of Chinese, Cantonese has some emotional expressions that are only used by Cantonese speakers. Previous work on Chinese emotional vocabularies focused primarily on Mandarin. However, little is known about Cantonese emotion vocabularies. This is important since both language variants might have distinct emotional expressions, despite sharing the same writing system. To explore the structure and organization of Cantonese-label emotion words, we selected 79 highly representative emotion cue words from an ongoing large-scale Cantonese word association study (SWOW-HK). We aimed to identify the categories of these emotion words and non-emotion words that related to emotion concepts. Hierarchical cluster analysis was used to generate word clusters and investigate the underlying emotion dimensions. As the cluster quality was low in hierarchical clustering, we further constructed an emotion graph using a network approach to explore how emotions are organized in the Cantonese mental lexicon. With the support of emotion knowledge, the emotion graph defined more distinct emotion categories. The identified network communities covered basic emotions such as love, happiness, and sadness. Our results demonstrate that mental lexicon graphs constructed from free associations of Cantonese emotion-label words can reveal fine categories of emotions and their relevant concepts