A Prompt-Guided and Quality-Aware Robust Text-Audio Intent Recognition Framework for Elderly Care.

Zhimin Wei, Shuhao Tian, Yanzhen Wang, Yao Wang, Xiaolong Zhou, Jianyong Li

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.

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1 · What the graph read from it

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5 · Who and what money

Authors and funding

6 authors.

Zhimin WeiCollege of Mechanical Engineering, Beihua University, Jilin 132021, China.ORCID 0009-0002-6497-6662

Shuhao TianCollege of Mechanical Engineering, Beihua University, Jilin 132021, China.

Yanzhen WangCollege of Mechanical Engineering, Beihua University, Jilin 132021, China.

Yao WangCollege of Mechanical Engineering, Beihua University, Jilin 132021, China.ORCID 0000-0002-7310-544X

Xiaolong ZhouCollege of Mechanical Engineering, Beihua University, Jilin 132021, China.ORCID 0000-0002-0934-6046

Jianyong LiCollege of Mechanical Engineering, Beihua University, Jilin 132021, China.

Funding

Department of Education of Jilin Province 20240401082YYJilin Province Science and Technology Department 20240401082YY

6 · The paper itself

Abstract

In natural language understanding, intent recognition plays a central role in human-computer interaction. However, in elderly-care scenarios, acoustic signals are often affected by atypical speech patterns, slower speaking rates, and environmental noise, making audio information less reliable and reducing the effectiveness of conventional text-audio fusion methods. To address this problem, we propose a prompt-guided and quality-aware text-audio intent recognition framework. Specifically, a

Indexed as

IntentionPattern Recognition, AutomatedAcousticsAgedAlgorithmsHumansacoustic degradationelderly-care interactionmultimodal intent recognitionquality-aware fusion

Identifiers

PMID42655541

DOI10.3390/s26165233

PMCPMC13517858

What Socratic holds

Textmetadata

Read underepoch 390

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 Socratic graph.