Context and NLP

Hung, Victor

doi:10.1007/978-1-4939-1887-4_10

Cited by 2 publications

(2 citation statements)

References 23 publications

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“…Google's AI blog, we hear how the AI addresses a number of issues that have plagued chatbot development, by extending functionality to include features of 'natural' conversations such as elaborations, pauses, and interruptions (Leviathan & Matias 2018). Although Duplex is a highly optimized model in this regard, the research supporting this shift in NLP has been underway for a few years and is known as context-centric architecture (Hung 2014). Here, context is understood as cues given by the larger linguistic environment or situation in which a conversation is occurring to resolving syntactical or semantic ambiguities (Hung 2014, 144-5).…”

Section: In Recorded Interactions Between Duplex and A Human Caller Onmentioning

confidence: 99%

Disfluent Interfaces. Affective Conversations: Differencing Humans and Machines in AI

Münster¹

2021

Affects, Interfaces, Events

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For much of the relatively short history of computational interfaces, designers have emphasized the importance of naturalism and its place in aiding ease of exchange between humans and computers. In the musings and applications of Donald Norman (1990), Allan Kay (1990), and a generation of human-computer interaction (HCI) thinkers and engineers throughout the 1980s, the desired aim for human-computer interaction was the erasure of a physical and existential space that maintained the distinction between computation and human agents. Many of these early currents in HCI fell into two camps in their approaches to, for example, the centrality of interfaces in computation. On the one hand, an interface such as a GUI was seen-and has increasingly been involved in web design, for example-as the location to imagistically instantiate representations of the 'intuitive' actions and perceptions of humans with metaphors from the backend of computational processes (see for example, Kay 1990). On the other hand, beginning with Kay's critique of the GUI (1990, 210), the visible interface has often been seen as something that should be progressively erased. However, what was common to and continues to persist as the key vector to conceiving the relation of computation to human action and perception is that the space of engagement across, between, or amid computer and human requires naturalizing.

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Section: In Recorded Interactions Between Duplex and A Human Caller Onmentioning

confidence: 99%

Disfluent Interfaces. Affective Conversations: Differencing Humans and Machines in AI

Münster¹

2021

Affects, Interfaces, Events

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“…In recorded interactions between Duplex and a human caller on Google's AI blog, we hear how the AI addresses a number of issues that have plagued chatbot development, by extending functionality to include features of 'natural' conversations such as elaborations, pauses, and interruptions (Leviathan & Matias 2018). Although Duplex is a highly optimized model in this regard, the research supporting this shift in NLP has been underway for a few years and is known as context-centric architecture (Hung 2014). Here, context is understood as cues given by the larger linguistic environment or situation in which a conversation is occurring to resolving syntactical or semantic ambiguities (Hung 2014, 144-5).…”

Section: Ai and Its Socio-cultural Materialitiesmentioning

confidence: 99%

Affects, Interfaces, Events

2021

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This book engages with how affective encounters are shaped and conditioned by interfacial events. Together, the chapters explore the implications of this on a micro-perceptual and macro-relational level through an experimental middling of approaches and examples. While broadly departing from a Spinozist and Deleuzian theoretical foundation, the book weaves together a compelling number of conceptual and empirical trajectories. Always attuned to the implications, modulations and tonalities arising in the readings through art, journalism, bodies, an/archives, data and design, Affects, Interfaces, Events allows for a truly transdisciplinary resonance driven by theory, technology and practice.

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Context and NLP

Cited by 2 publications

References 23 publications

Disfluent Interfaces. Affective Conversations: Differencing Humans and Machines in AI

Disfluent Interfaces. Affective Conversations: Differencing Humans and Machines in AI

Affects, Interfaces, Events

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