Evidence map›Paper›PMID 41682568›Full record

ArticleSensors (Basel, Switzerland)2026

Music Performance Improvement Support System Using a Semi-Automated Instrument-Playing Robot with Real-Time Acoustic Analysis and Habit Visualization.

Kouki Tomiyoshi, Hiroaki Sonoda, Hikari Kuriyama, Gou Koutaki

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 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.

Kouki TomiyoshiGraduate School of Science and Technology, Kumamoto University, Kumamoto 860-8555, Japan.ORCID 0009-0006-3486-0158
Hiroaki SonodaGraduate School of Science and Technology, Kumamoto University, Kumamoto 860-8555, Japan.ORCID 0009-0003-9601-8036
Hikari KuriyamaGraduate School of Science and Technology, Kumamoto University, Kumamoto 860-8555, Japan.ORCID 0009-0006-3149-3399
Gou KoutakiDepartment of Computer Science and Electrical Engineering, Kumamoto University, Kumamoto 860-8555, Japan.ORCID 0000-0002-3414-1085

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This paper proposes an acoustic analysis system to help improve saxophone performance skills. The system combines direct support for performance movements by a robot with indirect support by presenting performance information. By sensing the performance audio and performing real-time acoustic analysis, the system presents the learner with information about their performance and their playing habits. The performance information presented to the learner includes pitch, volume, and playing timing. For performance habit analysis, a Markov model with pitch as the state and an internal probability parameter that indicates the quality of the performance evaluation as the pitch transitions are defined. In the experiment, we conducted a pilot study targeting experienced saxophone players and a beginner saxophone player to verify the effectiveness of the proposed system. The experiment showed that the MAE of the played pitch was significantly reduced by using the proposed system.

Indexed as

music performance analysisplayer’s habit analysiswoodwind instruments

Identifiers

PMID41682568
PMCPMC12900130

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

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.