mlsanityData to 7 Oct 2026

STUDIES: Corpus of Japanese Empathetic Dialogue Speech Towards Friendly Voice Agent

arXiv 2203.14757 ↗First posted 28 Mar 2022cs.SD cs.AI cs.CLcited by 9

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Abstract (arXiv)

We present STUDIES, a new speech corpus for developing a voice agent that can speak in a friendly manner. Humans naturally control their speech prosody to empathize with each other. By incorporating this "empathetic dialogue" behavior into a spoken dialogue system, we can develop a voice agent that can respond to a user more naturally. We designed the STUDIES corpus to include a speaker who speaks with empathy for the interlocutor's emotion explicitly. We describe our methodology to construct an empathetic dialogue speech corpus and report the analysis results of the STUDIES corpus. We conducted a text-to-speech experiment to initially investigate how we can develop more natural voice agent that can tune its speaking style corresponding to the interlocutor's emotion. The results show that the use of interlocutor's emotion label and conversational context embedding can produce speech with the same degree of naturalness as that synthesized by using the agent's emotion label. Our project page of the STUDIES corpus is http://sython.org/Corpus/STUDIES.

Key facts. Cited by 9 papers in the map (data through 7 Oct 2026). Builds on 14 of its 34 references that are in the map. First posted on arXiv 28 Mar 2022.

Builds on

14 of 34 references.

References · 14

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2 more
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Cited by year (2026 to 7 Oct)

Citing papers per year: 2022: 1; 2023: 3; 2024: 1; 2025: 1; 2026: 3.

9 papers.

  1. 2023ChatGPT-EDSS: Empathetic Dialogue Speech Synthesis Trained from ChatGPT-derived Context Word Embeddingscited by 4
  2. 2022Acoustic Modeling for End-to-End Empathetic Dialogue Speech Synthesis Using Linguistic and Prosodic Contexts of Dialogue Historycited by 3
  3. 2023CALLS: Japanese Empathetic Dialogue Speech Corpus of Complaint Handling and Attentive Listening in Customer Centercited by 3
  4. 2023Towards Generalizable SER: Soft Labeling and Data Augmentation for Modeling Temporal Emotion Shifts in Large-Scale Multilingual Speechcited by 2
  5. 2024J-CHAT: Japanese Large-scale Spoken Dialogue Corpus for Spoken Dialogue Language Modelingcited by 2
  6. 2025SpeechDialogueFactory: Generating High-Quality Speech Dialogue Data to Accelerate Your Speech-LLM Developmentcited by 1
  7. 2026EmplifAI: a Fine-grained Dataset for Japanese Empathetic Medical Dialogues in 28 Emotion Labelscited by 0
  8. 2026Emotion Recognition in Sign Language Conversationcited by 0
  9. 2026Let Me Look at You: Advanced Facial Expression Modeling for Conversational Speech Synthesiscited by 0