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Dehumanizing Voice Technology: Phonetic & Experiential Consequences of Restricted Human-Machine Interaction

arXiv 2111.01934 ↗First posted 2 Nov 2021cs.AI cs.HCcited by 0

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Abstract (arXiv)

The use of natural language and voice-based interfaces gradu-ally transforms how consumers search, shop, and express their preferences. The current work explores how changes in the syntactical structure of the interaction with conversational interfaces (command vs. request based expression modalities) negatively affects consumers' subjective task enjoyment and systematically alters objective vocal features in the human voice. We show that requests (vs. commands) lead to an in-crease in phonetic convergence and lower phonetic latency, and ultimately a more natural task experience for consumers. To the best of our knowledge, this is the first work docu-menting that altering the input modality of how consumers interact with smart objects systematically affects consumers' IoT experience. We provide evidence that altering the required input to initiate a conversation with smart objects provokes systematic changes both in terms of consumers' subjective experience and objective phonetic changes in the human voice. The current research also makes a methodological con-tribution by highlighting the unexplored potential of feature extraction in human voice as a novel data format linking consumers' vocal features during speech formation and their sub-jective task experiences.

Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 1 of its 12 references that are in the map. First posted on arXiv 2 Nov 2021.

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References · 1

  1. 2017A Deep Reinforcement Learning Chatbotcited by 36

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