SeniorTalk: A Chinese Conversation Dataset with Rich Annotations for Super-Aged Seniors

Yang Chen, Hui Wang, shiyao wang, Junyang Chen, Jiabei He, Jiaming Zhou, Xi Yang, Yequan Wang, Yonghua Lin, Yong Qin

Keywords: natural conversation; chinese speech data; elderly speech; speech recognition

TL;DR: This paper presents SeniorTalk, a Chinese conversation dataset focused on speech from people aged 75 and older, supporting various speech tasks.

Abstract: While voice technologies increasingly serve aging populations, current systems exhibit significant performance gaps due to inadequate training data capturing elderly-specific vocal characteristics like presbyphonia and dialectal variations. The limited data available on super-aged individuals in existing elderly speech datasets, coupled with overly simple recording styles and annotation dimensions, exacerbates this issue. To address the critical scarcity of speech data from individuals aged 75 and above, we introduce SeniorTalk, a carefully annotated Chinese spoken dialogue dataset. This dataset contains 55.53 hours of speech from 101 natural conversations involving 202 participants, ensuring a strategic balance across gender, region, and age. Through detailed annotation across multiple dimensions, it can support a wide range of speech tasks. We perform extensive experiments on speaker verification, speaker diarization, speech recognition, and speech editing tasks, offering crucial insights for the development of speech technologies targeting this age group. Code is available at https://github.com/flageval-baai/SeniorTalk and data at https://huggingface.co/datasets/evan0617/seniortalk.

Dataset URL: https://huggingface.co/datasets/evan0617/seniortalk

Code URL: https://github.com/flageval-baai/SeniorTalk

Primary Area: Applications of Datasets & Benchmarks for in speech and audio

Submission Number: 326