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SeniorTalk

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Automatic Speech Recognition
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Chinese
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metadata
license: cc-by-nc-sa-4.0
task_categories:
  - automatic-speech-recognition
language:
  - zh
pretty_name: SeniorTalk
size_categories:
  - 10K<n<100K
features:
  - name: audio
    dtype: audio
  - name: transcription
    dtype: string
  - name: speaker
    dtype: string
  - name: gender
    dtype: string
  - name: age
    dtype: string
  - name: location
    dtype: string
  - name: device
    dtype: string
extra_gated_prompt: >-
  This dataset is made available for academic and non-commercial research
  purposes only. By accessing or using the dataset, you agree to comply with the
  following terms and conditions:  

  1. The dataset may only be used for academic research and educational
  purposes. Any commercial use, including but not limited to commercial product
  development, commercial speech recognition services, or monetization of the
  dataset in any form, is strictly prohibited.  

  2. The dataset must not be used for any research or applications that may
  infringe upon the privacy rights of the recorded participants. Any attempt to
  re-identify participants or extract personally identifiable information from
  the dataset is strictly prohibited. Researchers must ensure that their use of
  the dataset aligns with ethical research practices and institutional review
  board (IRB) guidelines where applicable.  

  3. If a participant (or their legal guardian) requests the removal of their
  data from the dataset, all recipients of the dataset must comply by deleting
  the affected data from their records. Researchers must acknowledge that such
  withdrawal requests may occur and agree to take reasonable steps to ensure
  compliance.  

  4. The dataset, in whole or in part, may not be redistributed, resold, or
  shared with any third party. Each researcher or institution must independently
  request access to the dataset and agree to these terms.  

  5. Any published work (e.g., papers, reports, presentations) that uses this
  dataset must properly cite the dataset as specified in the accompanying
  documentation.  

  6. You may create derived works (e.g., processed versions of the dataset) for
  research purposes, but such derivatives must not be distributed beyond your
  research group without prior written permission from the dataset
  maintainers.  

  7. The dataset is provided "as is" without any warranties, express or implied.
  The dataset maintainers are not responsible for any direct or indirect
  consequences arising from the use of the dataset.  

  8. Failure to comply with these terms may result in revocation of dataset
  access. The dataset maintainers reserve the right to deny access to any
  individual or institution found in violation of these terms.  

  9. If the researcher is employed by a for-profit, commercial entity, the
  researcher's employer shall also be bound by these terms and conditions, and
  the researcher hereby represents that they are fully authorized to enter into
  this agreement on behalf of such employer.

  By requesting access to the dataset, you acknowledge that you have read,
  understood, and agreed to these terms.  
extra_gated_fields:
  Name: text
  Email: text
  Affiliation: text
  Position: text
  Your Supervisor/manager/director: text
  I agree to the Terms of Access: checkbox
  I agree to use this dataset for non-commercial use ONLY: checkbox

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

Hugging Face Datasets arXiv License: CC BY-NC-SA-4.0 Github

Introduction

SeniorTalk is a comprehensive, open-source Mandarin Chinese speech dataset specifically designed for research on elderly aged 75 to 85. This dataset addresses the critical lack of publicly available resources for this age group, enabling advancements in automatic speech recognition (ASR), speaker verification (SV), speaker dirazation (SD), speech editing and other related fields. The dataset is released under a CC BY-NC-SA 4.0 license, meaning it is available for non-commercial use.

Dataset Details

This dataset contains 55.53 hours of high-quality speech data collected from 202 elderly across 16 provinces in China. Key features of the dataset include:

  • Age Range: 75-85 years old (inclusive). This is a crucial age range often overlooked in speech datasets.
  • Speakers: 202 unique elderly speakers.
  • Geographic Diversity: Speakers from 16 of China's 34 provincial-level administrative divisions, capturing a range of regional accents.
  • Gender Balance: Approximately 7:13 representation of male and female speakers, largely attributed to the differing average ages of males and females among the elderly.
  • Recording Conditions: Recordings were made in quiet environments using a variety of smartphones (both Android and iPhone devices) to ensure real-world applicability.
  • Content: Natural, conversational speech during age-appropriate activities. The content is unrestricted, promoting spontaneous and natural interactions.
  • Audio Format: WAV files with a 16kHz sampling rate.
  • Transcriptions: Carefully crafted, character-level manual transcriptions.
  • Annotations: The dataset includes annotations for each utterance, and for the speakers level.
    • Session-level: sentence_start_time,sentence_end_time,overlapped speech
    • Utterance-level: id, accent_level, text (transcription).
    • Token-level: special token([SONANT],[MUSIC],[NOISE]....)
    • Speaker-level: speaker_id, age, gender, location (province), device.

Dataset Structure

Dialogue Dataset

The dataset is split into two subsets:

Split # Speakers # Dialogues Duration (hrs) Avg. Dialogue Length (h)
train 182 91 49.83 0.54
test 20 10 5.70 0.57
Total 202 101 55.53 0.55

The dataset file structure is as follows.


dialogue_data/  
├── wav  
│   ├── train/*.tar   
│   └── test/*.tar   
└── transcript/*.txt
UTTERANCEINFO.txt  # annotation of topics and duration
SPKINFO.txt   # annotation of location , age , gender and device

Each WAV file has a corresponding TXT file with the same name, containing its annotations.

For more details, please refer to our paper SeniorTalk.

ASR Dataset

The dataset is split into three subsets:

Split # Speakers # Utterances Duration (hrs) Avg. Utterance Length (s)
train 162 47,269 29.95 2.28
validation 20 6,891 4.09 2.14
test 20 5,869 3.77 2.31
Total 202 60,029 37.81 2.27

The dataset file structure is as follows.

sentence_data/  
├── wav  
│   ├── train/*.tar
│   ├── dev/*.tar 
│   └── test/*.tar   
└── transcript/*.txt   
UTTERANCEINFO.txt  # annotation of topics and duration
SPKINFO.txt   # annotation of location , age , gender and device

Each WAV file has a corresponding TXT, containing its annotations.

For more details, please refer to our paper SeniorTalk.

📚 Cite me 

@misc{chen2025seniortalkchineseconversationdataset,
      title={SeniorTalk: A Chinese Conversation Dataset with Rich Annotations for Super-Aged Seniors}, 
      author={Yang Chen and Hui Wang and Shiyao Wang and Junyang Chen and Jiabei He and Jiaming Zhou and Xi Yang and Yequan Wang and Yonghua Lin and Yong Qin},
      year={2025},
      eprint={2503.16578},
      archivePrefix={arXiv},
      primaryClass={cs.CL},
      url={https://arxiv.org/abs/2503.16578}, 
}