22 research outputs found
The social structure of signing communities and lexical variation:A cross-linguistic comparison of three unrelated sign languages
Claims have been made about the relationship between the degree of lexical variation and the social structure of a sign language community (e.g., population size), but to date there exist no large-scale cross-linguistic comparisons to address these claims. In this study, we present a cross-linguistic analysis of lexical variation in three signing communities: Kata Kolok, Israeli Sign Language (ISL) and British Sign Language (BSL). Contrary to the prediction that BSL would have the lowest degree of lexical variation because it has the largest population size, we found that BSL has the highest degree of lexical variation across the entire community (i.e., at the global level). We find, however, that BSL has the lowest degree of lexical variation at the local level, i.e., within clusters of participants who group most similarly lexically. Kata Kolok and ISL, on the other hand, exhibit less of a distinction between variation at the global and local levels, suggesting that lexical variation does not pattern as strongly within subsets of these two communities as does BSL. The results of this study require us to reassess claims made about lexical variation and community structure; we need to move towards an approach of studying (lexical) variation which treats communities equally on a theoretical level and which respects the unique social-demographic profile of each community when designing the analysis by using a community-centered approach.</p
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Understanding Music Interaction, and Why It Matters
This is the introductory chapter of a book dedicated to new research in, and emerging new understandings of, music and human-computer interaction—known for short as music interaction. Music interaction research plays a key role in innovative approaches to diverse musical activities, including performance, composition, education, analysis, production and collaborative music making. Music interaction is pivotal in new research directions in a range of activities, including audience participation, interaction between music and dancers, tools for algorithmic music, music video games, audio games, turntablism and live coding. More generally, music provides a powerful source of challenges and new ideas for human-computer interaction (HCI). This introductory chapter reviews the relationship between music and human-computer interaction and outlines research themes and issues that emerge from the collected work of researchers and practitioners in this book
Music and HCI
Music is an evolutionarily deep-rooted, abstract, real-time, complex, non-verbal, social activity. Consequently, interaction design in music can be a valuable source of challenges and new ideas for HCI. This workshop will reflect on the latest research in Music and HCI (Music Interaction for short), with the aim of strengthening the dialogue between the Music Interaction community and the wider HCI community. We will explore recent ideas from Music Interaction that may contribute new perspectives to general HCI practice, and conversely, recent HCI research in non-musical domains with implications for Music Interaction. We will also identify any concerns of Music Interaction that may require unique approaches. Contributors engaged in research in any area of Music Interaction or HCI who would like to contribute to a sustained widening of the dialogue between the distinctive concerns of the Music Interaction community and the wider HCI community will be welcome
Kata Kolok and Balinese homesigners social and lexical variation
In this repository, we provide the data and the analysis files for the analysis of social and lexical variation in Kata Kolok and Balinese homesigners. Please see the README.md/pdf file for more information on how to reproduce the analysis.</p
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Shared context and lexical alignment: an experimental investigation
What drives lexical alignment in the context of language emergence? We test the theory that limited context promotes alignment, because individuals cannot make use of iconic mappings between shared meanings and forms. Using a novel referential communication paradigm where participants use pre-recorded gesture videos to communicate, we test different context conditions. We find, unexpectedly, no alignment differences between dyads with shared context and dyads with limited context, even though the former have fewer communicative errors. Importantly, we do observe differences when it comes to the iconic strategies used: less shared context promotes the use of (shared) visual iconicity
deaf participants
deaf participant
hearing participants
hearing participant
Variation Project
Picture stimuli of five different semantic domains (animals, food, praying, colours, misc) were presented
Shared Context Facilitates Lexical Variation in Sign Language Emergence
It has been suggested that social structure affects the degree of lexical variation in sign language emergence. Evidence from signing communities supports this, with smaller, more insular communities typically displaying a higher degree of lexical variation compared to larger, more dispersed and diverse communities. Though several factors have been proposed to affect the degree of variation, here we focus on how shared context, facilitating the use of iconic signs, facilitates the retention of lexical variation in language emergence. As interlocutors with the same background have similar salient features for real world concepts, shared context allows for the successful communication of iconic mappings between form and culturally salient features (i.e., the meaning specific to an individual based on their cultural context). Because in this case the culturally salient features can be retrieved from the form, there is less pressure to converge on a single form for a concept. We operationalize the relationship between lexical variation and iconic affordances using an agent-based model, studying how shared context and also population size affects the degree of lexical variation in a population of agents. Our model provides support for the relationship between shared context, population size and lexical variation, though several extensions would help improve the explanatory power of this model