WildElder: A Chinese Elderly Speech Dataset from the Wild with Fine-Grained Manual Annotations

Fuente: arXiv
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Main Authors: Wang, Hui, Zhou, Jiaming, He, Jiabei, Sun, Haoqin, Qin, Yong
Format: Preprint
Published: 2025
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author Wang, Hui
Zhou, Jiaming
He, Jiabei
Sun, Haoqin
Qin, Yong
author_facet Wang, Hui
Zhou, Jiaming
He, Jiabei
Sun, Haoqin
Qin, Yong
contents Elderly speech poses unique challenges for automatic processing due to age-related changes such as slower articulation and vocal tremors. Existing Chinese datasets are mostly recorded in controlled environments, limiting their diversity and real-world applicability. To address this gap, we present WildElder, a Mandarin elderly speech corpus collected from online videos and enriched with fine-grained manual annotations, including transcription, speaker age, gender, and accent strength. Combining the realism of in-the-wild data with expert curation, WildElder enables robust research on automatic speech recognition and speaker profiling. Experimental results reveal both the difficulties of elderly speech recognition and the potential of WildElder as a challenging new benchmark. The dataset and code are available at https://github.com/NKU-HLT/WildElder.
format Preprint
id arxiv_https___arxiv_org_abs_2510_09344
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle WildElder: A Chinese Elderly Speech Dataset from the Wild with Fine-Grained Manual Annotations
Wang, Hui
Zhou, Jiaming
He, Jiabei
Sun, Haoqin
Qin, Yong
Sound
Audio and Speech Processing
Elderly speech poses unique challenges for automatic processing due to age-related changes such as slower articulation and vocal tremors. Existing Chinese datasets are mostly recorded in controlled environments, limiting their diversity and real-world applicability. To address this gap, we present WildElder, a Mandarin elderly speech corpus collected from online videos and enriched with fine-grained manual annotations, including transcription, speaker age, gender, and accent strength. Combining the realism of in-the-wild data with expert curation, WildElder enables robust research on automatic speech recognition and speaker profiling. Experimental results reveal both the difficulties of elderly speech recognition and the potential of WildElder as a challenging new benchmark. The dataset and code are available at https://github.com/NKU-HLT/WildElder.
title WildElder: A Chinese Elderly Speech Dataset from the Wild with Fine-Grained Manual Annotations
topic Sound
Audio and Speech Processing
url https://arxiv.org/abs/2510.09344