🇹🇭 THAI-SER Dataset 🎭

[📝 Paper (preprint)]

Published by: AI Research Institute of Thailand (AIResearch)

In collaboration with:

• Vidyasirimedhi Institute of Science and Technology (VISTEC)
• Digital Economy Promotion Agency (depa)
• Department of Computer Engineering, Faculty of Engineering, Chulalongkorn University
• Department of Dramatic Arts, Faculty of Arts, Chulalongkorn University

Sponsored by: Advanced Info Services Public Company Limited (AIS), and Siam Commercial Bank (SCB)

License: Creative Commons BY-SA 4.0

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🚀 Dataset Overview

THAI-SER is an open Thai speech emotion recognition dataset containing emotional speech utterances in Thai. This dataset includes recordings of professional actors performing scripted and improvised scenarios.

🌟 Key Highlights

• Total Duration: 41 hours 36 minutes
• Total Utterances: 27,854
• Number of Actors: 200 (112 female, 88 male)
• Recording Environments: Studio (controlled & uncontrolled), Zoom
• Emotions: Neutral, Anger, Happiness, Sadness, Frustration
• Session Types: Script Session, Improvisation Session

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🎙️ Recording Environments

The dataset comprises recordings from two main environments:

🎧 Studio Recordings

• Studio A: Noise-controlled, soundproof rooms (studio001 to studio018)
• Studio B: Normal rooms without soundproofing (studio019 to studio080)

💻 Zoom Recordings

• Online via Zoom and Zencastr (zoom001 to zoom020)

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📝 Session Details

📖 Script Session

Actors performed 3 predetermined sentences, each repeated twice per emotion with two emotional intensities (normal and strong), plus a neutral expression.

Sentence ID	Thai Sentence	English Translation
1	พรุ่งนี้มันวันหยุดราชการนะรู้รึยัง หยุดยาวด้วย	Do you know tomorrow is a public holiday and it's the long one.
2	อ่านหนังสือพิมพ์วันนี้รึยัง รู้ไหมเรื่องนั้นกลายเป็นข่าวใหญ่ไปแล้ว	Have you read today's newspaper? That story was the topliner.
3	ก่อนหน้านี้ก็ยังเห็นทำตัวปกติดี ใครจะไปรู้หล่ะ ว่าเค้าคิดแบบนั้น	He/She was acting normal recently; who would have thought they'd think like that?

🎬 Improvisation Session

Actors improvised conversations according to provided scenarios with specific emotions.

Scenarios	Actor A	Actor B
1	(Neutral) A hotel receptionist trying to explain and service the customer	(Angry) A angry customer who dissatisfy the hotel services
2	(Happy) A person excitingly talking with B about his/her marriage plan	(Happy) A person happily talking with A and help him/her plan his ceremony
3	(Sad) A patient feeling depressed	(Neutral) A doctor attempting to talk with A neutrally
4	(Angry) A furious boss talking with the employee	(Frustrated) A frustrated person attempting to argue with his/her boss
5	(Frustrated) A person frustratingly talk about another person's action	(Sad) A person feeling guilty and sad about his/her action
6	(Happy) A happy hotel staffs	(Happy) Happy customer
7	(Sad) A sad person who felt unsecured about the incoming marriage	(Frustrated) A person who frustrated about another person's insecureness
8	(Frustrated) A frustrated patience	(Neutral) A Doctor talking with the patience
9	(Neutral) A worker who assigned to tell his/her co-worker about the company's bad situation	(Sad) An employee feeling sad after listenning
10	(Angry) A person raging about another person's behavior	(Angry) A person who feels like being blamed by another person
11	(Frustrated) A director who unsatisfied co-worker	(Frustrated) A frustrated person who try their best on the job
12	(Happy) A person who gets a new job or promotion	(Sad) A person who desperate in his/her job
13	(Neutral) A patient inquire information	(Happy) A happy doctor telling his/her patience more information
14	(Angry) A person who upset with his/her work	(Neutral) A calm friend who listened to another person's problem
15	(Sad) A person sadly tell another person about a relationship	(Angry) A person who feels angry after listening to another person's bad relationship

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📋 Data Schema

The dataset includes detailed annotations and actor demographics (see header above).

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📊 Dataset Statistics

Recording Environment	Session	Utterances	Duration (hrs)
Zoom (20)	Script	2,398	4.03
	Improvisation	3,606	5.89
Studio (80)	Script	9,582	13.69
	Improvisation	12,268	18.01
Total (100)	Both	27,854	41.61

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📄 Paper

The associated research paper will be available soon at link will be updated soon.

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💻 Code for Experiments

Experiment code is available on GitHub.

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🔖 Version

• Version 2.0 (April 15, 2025): Fixed majority agreement calculation.
• Version 1.0 (March 26, 2021): Initial release.

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📌 Citation

Please cite this dataset as:

@misc{wongpithayadisai2025thaispeechemotionrecognition,
      title={THAI Speech Emotion Recognition (THAI-SER) corpus}, 
      author={Jilamika Wongpithayadisai and Chompakorn Chaksangchaichot and Soravitt Sangnark and Patawee Prakrankamanant and Krit Gangwanpongpun and Siwa Boonpunmongkol and Premmarin Milindasuta and Dangkamon Na-Pombejra and Sarana Nutanong and Ekapol Chuangsuwanich},
      year={2025},
      eprint={2507.09618},
      archivePrefix={arXiv},
      primaryClass={cs.SD},
      url={https://arxiv.org/abs/2507.09618}, 
}