Evidence map›Paper›PMID 42303649›Full record

ArticleScientific reports2026

Verification of the factors of individuality through avatar's speech generation system.

Yuya Komai, Takahisa Uchida, Hiroko Kamide, Hiroshi Ishiguro

Abstract read
In one paragraph

Article in Scientific reports, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Yuya KomaiOsaka University, Osaka, Japan. komai.yuya@irl.sys.es.osaka-u.ac.jp.
Takahisa UchidaOsaka University, Osaka, Japan.
Hiroko KamideKyoto University, Kyoto, Japan.
Hiroshi IshiguroOsaka University, Osaka, Japan.

Funding

Moonshot Research and Development Program JPMJMS2011
6 · The paper itself

Abstract

In recent years, extensive research has been conducted on avatars, and multiple studies have demonstrated their effectiveness as a medium for remote operation. While avatars are effective when teleoperated, they must also be capable of autonomous behavior in the absence of an operator. In particular, avatars whose appearance closely resembles that of a real individual need to possess conversational abilities that reflect the personality of the person being modeled. This paper presents the development of a speech generation system that produces personality-consistent utterances using a large language model (LLM) and speech synthesis technology. We call this system AvatarLLM. Through system evaluation, we examined the factors contributing to the perception of individuality. Experimental results indicated that the utterances generated by AvatarLLM were perceived as more likely reproducing the modeled individual than those of the actual person. Furthermore, we found that the perceived identity of the utterances could influence the perceived identity of the voice itself.

Indexed as

AvatarIndividualitySpeechHumansLarge Language Models

Identifiers

PMID42303649
PMCPMC13272814

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.