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VOTE400(Voide Of The Elderly 400 Hours): A Speech Dataset to Study Voice Interface for Elderly-Care

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arxiv 2101.11469 v1 pith:7XH4HAZI submitted 2021-01-20 eess.AS cs.CLcs.SD

Minsu Jang , Sangwon Seo , Dohyung Kim , Jaeyeon Lee , Jaehong Kim , Jun-Hwan Ahn This is my paper
classification eess.AScs.CLcs.SD
keywords speechelderlydatasethourspeoplerecognitionvote400elderly-care
verification ladder T0 review T1 audit T2 compute T3 formal
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This paper introduces a large-scale Korean speech dataset, called VOTE400, that can be used for analyzing and recognizing voices of the elderly people. The dataset includes about 300 hours of continuous dialog speech and 100 hours of read speech, both recorded by the elderly people aged 65 years or over. A preliminary experiment showed that speech recognition system trained with VOTE400 can outperform conventional systems in speech recognition of elderly people's voice. This work is a multi-organizational effort led by ETRI and MINDs Lab Inc. for the purpose of advancing the speech recognition performance of the elderly-care robots.

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Cited by 1 Pith paper

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  1. Elderly-Contextual Data Augmentation via Speech Synthesis for Elderly ASR

    cs.CL 2026-04 unverdicted novelty 5.0 of 10

    Combining LLM-based elderly-contextual paraphrasing with TTS synthesis using elderly speakers reduces word error rates in elderly ASR by up to 58% over standard Whisper baselines on English and Korean datasets.

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