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Datasets:
Gaphy
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ECD-TSE

Tasks:
Text-to-Speech
Languages:
English
Size:
100M<n<1B
ArXiv:
Tags:
emotion
License:
Dataset card Files
xet
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The information you provide will be collected, stored and processed by S2LAB.

Subject to other terms:

  1. The corpus is not used for commercial purposes and is only provided free of charge to “universities and research institutes” for scientific research.

  2. When publishing papers and applying for results, if you use this dataset, please indicate the reference:

    @article{liu2025towards,
    title={Towards Emotionally Consistent Text-Based Speech Editing: Introducing EmoCorrector and The ECD-TSE Dataset},
    author={Liu, Rui and Gao, Pu and Xi, Jiatian and Sisman, Berrak and Busso, Carlos and Li, Haizhou},
    journal={arXiv preprint arXiv:2505.20341},
    year={2025}
    }

  3. The final interpretation of this corpus belongs to S2LAB Lab, Inner Mongolia University, China.

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ECD-TSE

ECD-TSE Overview

The prominent aspect of ECD-TSE is its inclusion of paired data featuring diverse text variations and a range of emotional expressions. ECD-TSE encompasses several topics.

Attribute Value
Speech Samples 84,000 = 1,400 * 5 * 12
Emotions 5 (Happy, Sadness, Neutral, Angry, Fear)
Speakers 12 (6 male and 6 female)
Text 7,000 = 1,400 * 5
Total Duration Approximately 90 hours
Sampling Rate 16,000 Hz
Speakers TTS Model Original Dataset
Speaker 1-5 Azure
Speaker 6-10 Cosyvoice ESD
Speaker 11-12 F5-TTS MEAD
Topics Description
Daily Life Sentences describing everyday activities, habits, and common events
Social Interaction Sentences involving communication, dialogue, and interaction between people.
Natural Environment Sentences describing natural phenomena, plants, animals, and environmental features.
Narrative/Storytelling Sentences likely extracted from novels, fairy tales, or other narrative texts, containing plots and characters.
Telephone Communication Including customer service, business calls, etc.
News Broadcast Current affairs news, weather forecasts, etc.
Meeting Minutes Discussions, summaries, decisions, etc.
Education Teaching materials, learning materials, language learning dialogues, etc.
Technology Including technical terminology, product introductions, research discussions, industry trends, etc.
Medicine Covering medical terminology, diagnoses, treatment plans, patient communication, etc.
Law Involving legal provisions, case analyses, legal consultations, court proceedings, etc.

Citations

If you find this dataset useful in your research, please consider citing the following paper:

@article{liu2025towards,
  title={Towards Emotionally Consistent Text-Based Speech Editing: Introducing EmoCorrector and The ECD-TSE Dataset},
  author={Liu, Rui and Gao, Pu and Xi, Jiatian and Sisman, Berrak and Busso, Carlos and Li, Haizhou},
  journal={arXiv preprint arXiv:2505.20341},
  year={2025}
}
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