Talking to Extraordinary Objects: Folktales Offer Analogies for Interacting with Technology
- URL: http://arxiv.org/abs/2601.06372v1
- Date: Sat, 10 Jan 2026 01:04:24 GMT
- Title: Talking to Extraordinary Objects: Folktales Offer Analogies for Interacting with Technology
- Authors: Martha Larson,
- Abstract summary: In the world of folktales, language is everywhere and talking to extraordinary objects is not unusual.<n>This overview presents examples of the analogies that folktales offer.
- Score: 0.0
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: Speech and language are valuable for interacting with technology. It would be ideal to be able to decouple their use from anthropomorphization, which has recently met an important moment of reckoning. In the world of folktales, language is everywhere and talking to extraordinary objects is not unusual. This overview presents examples of the analogies that folktales offer. Extraordinary objects in folktales are diverse and also memorable. Language capacity and intelligence are not always connected to humanness. Consideration of folktales can offer inspiration and insight for using speech and language for interacting with technology.
Related papers
- Proceedings of the ISCA/ITG Workshop on Diversity in Large Speech and Language Models [11.46358189300007]
Modern techniques rely on large models for representing general knowledge of one or several languages.<n>When humans interact with such technologies, the effectiveness of the interaction will be influenced by how far humans make use of the same type of language.
arXiv Detail & Related papers (2025-03-12T17:58:57Z) - A Taxonomy of Linguistic Expressions That Contribute To Anthropomorphism of Language Technologies [55.99010491370177]
anthropomorphism is the attribution of human-like qualities to non-human objects or entities.<n>To productively discuss the impacts of anthropomorphism, we need a shared vocabulary for the vast variety of ways that language can bemorphic.
arXiv Detail & Related papers (2025-02-14T02:43:46Z) - The Language of Motion: Unifying Verbal and Non-verbal Language of 3D Human Motion [46.01825432018138]
We propose a novel framework that unifies verbal and non-verbal language using multimodal language models.<n>Our model achieves state-of-the-art performance on co-speech gesture generation.<n>We believe unifying the verbal and non-verbal language of human motion is essential for real-world applications.
arXiv Detail & Related papers (2024-12-13T19:33:48Z) - Empirical evidence of Large Language Model's influence on human spoken communication [23.893223314507477]
We study whether cultural patterns transmit into human language, and ultimately shape human culture.<n>We apply causal inference techniques to 740,249 hours of human discourse from 360,445 YouTube academic talks and 771,591 conversational podcast episodes.<n>We detect a measurable and abrupt increase in the use of words preferentially generated by ChatGPT, such as delve, comprehend, boast, swift, and meticulous.<n>This marks the beginning of a closed cultural feedback loop in which cultural traits circulate bidirectionally between humans and machines.
arXiv Detail & Related papers (2024-09-03T10:01:51Z) - Learning and communication pressures in neural networks: Lessons from emergent communication [5.371337604556311]
We look at three cases where mismatches between the emergent linguistic behavior of neural agents and humans were resolved.<n>We identify key pressures at play for language learning and emergence: communicative success, production effort, learnability, and other psycho-/sociolinguistic factors.
arXiv Detail & Related papers (2024-03-21T14:33:34Z) - Learning to Model the World with Language [100.76069091703505]
To interact with humans and act in the world, agents need to understand the range of language that people use and relate it to the visual world.
Our key idea is that agents should interpret such diverse language as a signal that helps them predict the future.
We instantiate this in Dynalang, an agent that learns a multimodal world model to predict future text and image representations.
arXiv Detail & Related papers (2023-07-31T17:57:49Z) - Analyzing Folktales of Different Regions Using Topic Modeling and
Clustering [2.2559617939136505]
This paper employs two major natural language processing techniques, topic modeling and clustering, to find patterns in folktales.
We show that the common trends between folktales are family, food, traditional gender roles, mythological figures, and animals.
Our results demonstrate the prevalence of certain elements in cultures across the world.
arXiv Detail & Related papers (2022-06-09T02:04:18Z) - CPED: A Large-Scale Chinese Personalized and Emotional Dialogue Dataset
for Conversational AI [48.67259855309959]
Most existing datasets for conversational AI ignore human personalities and emotions.
We propose CPED, a large-scale Chinese personalized and emotional dialogue dataset.
CPED contains more than 12K dialogues of 392 speakers from 40 TV shows.
arXiv Detail & Related papers (2022-05-29T17:45:12Z) - Emergence of Machine Language: Towards Symbolic Intelligence with Neural
Networks [73.94290462239061]
We propose to combine symbolism and connectionism principles by using neural networks to derive a discrete representation.
By designing an interactive environment and task, we demonstrated that machines could generate a spontaneous, flexible, and semantic language.
arXiv Detail & Related papers (2022-01-14T14:54:58Z) - Learning Triadic Belief Dynamics in Nonverbal Communication from Videos [81.42305032083716]
Nonverbal communication can convey rich social information among agents.
In this paper, we incorporate different nonverbal communication cues to represent, model, learn, and infer agents' mental states.
arXiv Detail & Related papers (2021-04-07T00:52:04Z) - Annotation of Emotion Carriers in Personal Narratives [69.07034604580214]
We are interested in the problem of understanding personal narratives (PN) - spoken or written - recollections of facts, events, and thoughts.
In PN, emotion carriers are the speech or text segments that best explain the emotional state of the user.
This work proposes and evaluates an annotation model for identifying emotion carriers in spoken personal narratives.
arXiv Detail & Related papers (2020-02-27T15:42:39Z)
This list is automatically generated from the titles and abstracts of the papers in this site.
This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.