Pith. sign in

REVIEW 1 cited by

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

Not yet reviewed by Pith; the record is open.

This paper has not been read by Pith yet. Machine review is queued; the pith claim, tier, and objections will appear here once it completes.

SPECIMEN: schema-true, not a live event

T0 review · schema-true

One-sentence machine reading of the paper's core claim.

pith:XXXXXXXX · record.json · timestamp

arxiv 2203.14757 v2 pith:QGXHDX75 submitted 2022-03-28 cs.SD cs.AIcs.CLcs.HCcs.LG

classification cs.SDcs.AIcs.CLcs.HCcs.LG
keywords corpusstudiesagentspeechdialogueemotionvoiceempathetic
verification ladder T0 review T1 audit T2 compute T3 formal

Signed reviews

No signed human review yet.

0 comments
read the original abstract

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.

Discussion (0). Continue with ORCID to comment.

Forward citations

Cited by 1 Pith paper

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. Let Me Look at You: Advanced Facial Expression Modeling for Conversational Speech Synthesis

    cs.HC 2026-07 conditional novelty 6.0 of 10

    AU-supervised single-token face encoding plus dual visual–speech DPO on a large real-conversation dataset improves empathetic conversational TTS over text/speech-only and prior visual CSS systems.

Pith tools