Inter(sectional) Alia(s): Ambiguity in Voice Agent Identity via Intersectional Japanese Self-Referents

• URL: http://arxiv.org/abs/2506.01998v1
• Date: Tue, 20 May 2025 05:45:09 GMT
• Title: Inter(sectional) Alia(s): Ambiguity in Voice Agent Identity via Intersectional Japanese Self-Referents
• Authors: Takao Fujii, Katie Seaborn, Madeleine Steeds, Jun Kato,
• Abstract summary: The role of other "neutral" non-pronominal self-referents and voice as a socially expressive medium remains unexplored.<n>We found strong evidence of voice gendering alongside the potential of intersectional self-referents to evade gendering.<n>This work provides a nuanced take on agent identity perceptions and champions intersectional and culturally-sensitive work on voice agents.
• Score: 26.175369964227812
• License: http://creativecommons.org/licenses/by-nc-sa/4.0/
• Abstract: Conversational agents that mimic people have raised questions about the ethics of anthropomorphizing machines with human social identity cues. Critics have also questioned assumptions of identity neutrality in humanlike agents. Recent work has revealed that intersectional Japanese pronouns can elicit complex and sometimes evasive impressions of agent identity. Yet, the role of other "neutral" non-pronominal self-referents (NPSR) and voice as a socially expressive medium remains unexplored. In a crowdsourcing study, Japanese participants (N = 204) evaluated three ChatGPT voices (Juniper, Breeze, and Ember) using seven self-referents. We found strong evidence of voice gendering alongside the potential of intersectional self-referents to evade gendering, i.e., ambiguity through neutrality and elusiveness. Notably, perceptions of age and formality intersected with gendering as per sociolinguistic theories, especially boku and watakushi. This work provides a nuanced take on agent identity perceptions and champions intersectional and culturally-sensitive work on voice agents.

Related papers

• When Harry Meets Superman: The Role of The Interlocutor in Persona-Based Dialogue Generation [18.650805984660707]
  Endowing dialogue agents with persona information has proven to significantly improve the consistency and diversity of their generations.<n>While much focus has been placed on aligning dialogues with provided personas, the adaptation to the interlocutor's profile remains largely underexplored.<n>We investigate three key aspects: (1) a model's ability to align responses with both the provided persona and the interlocutor's; (2) its robustness when dealing with familiar versus unfamiliar interlocutors and topics, and (3) the impact of additional fine-tuning on specific persona-based dialogues.
  arXiv  Detail & Related papers  (2025-05-30T14:04:30Z)
• Sentient Agent as a Judge: Evaluating Higher-Order Social Cognition in Large Language Models [75.85319609088354]
  Sentient Agent as a Judge (SAGE) is an evaluation framework for large language models.<n>SAGE instantiates a Sentient Agent that simulates human-like emotional changes and inner thoughts during interaction.<n>SAGE provides a principled, scalable and interpretable tool for tracking progress toward genuinely empathetic and socially adept language agents.
  arXiv  Detail & Related papers  (2025-05-01T19:06:10Z)
• Disentangle Identity, Cooperate Emotion: Correlation-Aware Emotional Talking Portrait Generation [63.94836524433559]
  DICE-Talk is a framework for disentangling identity with emotion and cooperating emotions with similar characteristics.<n>We develop a disentangled emotion embedder that jointly models audio-visual emotional cues through cross-modal attention.<n>Second, we introduce a correlation-enhanced emotion conditioning module with learnable Emotion Banks.<n>Third, we design an emotion discrimination objective that enforces affective consistency during the diffusion process.
  arXiv  Detail & Related papers  (2025-04-25T05:28:21Z)
• Can LLM Agents Maintain a Persona in Discourse? [3.286711575862228]
  Large Language Models (LLMs) are widely used as conversational agents, exploiting their capabilities in various sectors such as education, law, medicine, and more.<n>LLMs are often subjected to context-shifting behaviour, resulting in a lack of consistent and interpretable personality-aligned interactions.<n>We show that while LLMs can be guided toward personality-driven dialogue, their ability to maintain personality traits varies significantly depending on the combination of models and discourse settings.
  arXiv  Detail & Related papers  (2025-02-17T14:36:39Z)
• Revealing Personality Traits: A New Benchmark Dataset for Explainable Personality Recognition on Dialogues [63.936654900356004]
  Personality recognition aims to identify the personality traits implied in user data such as dialogues and social media posts. We propose a novel task named Explainable Personality Recognition, aiming to reveal the reasoning process as supporting evidence of the personality trait.
  arXiv  Detail & Related papers  (2024-09-29T14:41:43Z)
• Silver-Tongued and Sundry: Exploring Intersectional Pronouns with ChatGPT [25.5053022752019]
  We studied the case of identity simulation through Japanese first-person pronouns. Pronouns evoke perceptions of social identities in ChatGPT at the intersections of gender, age, region, and formality. This work highlights the importance of pronoun use for social identity simulation, provides a language-based methodology for culturally-sensitive persona development, and advances the potential of intersectional identities in intelligent agents.
  arXiv  Detail & Related papers  (2024-05-13T23:38:50Z)
• "I'm fully who I am": Towards Centering Transgender and Non-Binary Voices to Measure Biases in Open Language Generation [69.25368160338043]
  Transgender and non-binary (TGNB) individuals disproportionately experience discrimination and exclusion from daily life. We assess how the social reality surrounding experienced marginalization of TGNB persons contributes to and persists within Open Language Generation. We introduce TANGO, a dataset of template-based real-world text curated from a TGNB-oriented community.
  arXiv  Detail & Related papers  (2023-05-17T04:21:45Z)
• Generating Multilingual Gender-Ambiguous Text-to-Speech Voices [4.005334718121374]
  This work addresses the task of generating novel gender-ambiguous TTS voices in a multi-speaker, multilingual setting. To our knowledge, this is the first systematic and validated approach that can reliably generate a variety of gender-ambiguous voices.
  arXiv  Detail & Related papers  (2022-11-01T10:40:24Z)
• Towards Socially Intelligent Agents with Mental State Transition and Human Utility [97.01430011496576]
  We propose to incorporate a mental state and utility model into dialogue agents. The hybrid mental state extracts information from both the dialogue and event observations. The utility model is a ranking model that learns human preferences from a crowd-sourced social commonsense dataset.
  arXiv  Detail & Related papers  (2021-03-12T00:06:51Z)
• Listener's Social Identity Matters in Personalised Response Generation [19.35779310590447]
  We investigate how the listener's identity influences the language used in Chinese dialogues on social media. The experiment results demonstrate that the listener's identity indeed matters in the language use of responses. By additionally modelling the listener's identity, the personalised response generator performs better in its own identity.
  arXiv  Detail & Related papers  (2020-10-27T14:57:21Z)
• Will I Sound Like Me? Improving Persona Consistency in Dialogues through Pragmatic Self-Consciousness [62.55060760615656]
  Recent models tackling consistency often train with additional Natural Language Inference (NLI) labels or attach trained extra modules to the generative agent for maintaining consistency. Inspired by social cognition and pragmatics, we endow existing dialogue agents with public self-consciousness on the fly through an imaginary listener. Our approach, based on the Rational Speech Acts framework, can enforce dialogue agents to refrain from uttering contradiction.
  arXiv  Detail & Related papers  (2020-04-13T08:16:16Z)

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.