emota-loader 2.0.0

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📦 emota_loader — Python Dataloader for EmoTa Dataset

EmoTa: A Tamil Emotional Speech Dataset (Thevakumar et al., CHiPSAL 2025) is the first open-access emotional speech corpus in Tamil, designed to capture the dialectal diversity of Sri Lankan Tamil speakers[^1].

Statistic	Value
Utterances	936 (22 speakers × 19 sentences × 5 emotions)
Speakers	22 native Sri Lankan Tamil (11 male, 11 female)
Sentences	19 semantically neutral sentences
Emotions	angry, happy, sad, fear, neutral
Inter-annotator Agreement	Fleiss’ Kappa = 0.74
Baseline F1 Scores	XGBoost: 0.91, Random Forest: 0.90

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🔧 Installation

You can install the package from PyPI using:

pip install emota_loader

Make sure to download the EmoTa dataset separately and point the loader to its root directory.

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🚀 Sample Usage

from emota_loader import EmoTaDataset

# Point to extracted dataset root folder
dataset = EmoTaDataset(root_dir="path/to/EmoTa").samples

print(f"Loaded {len(dataset)} samples")

sample = dataset[0]
print(f"  Audio Path      : {sample.audio_path}")
print(f"  Speaker ID      : {sample.speaker_id}")
print(f"  Speaker Gender  : {sample.speaker_gender}")
print(f"  Speaker Age     : {sample.speaker_age}")
print(f"  Speaker Region  : {sample.speaker_region}")
print(f"  Sentence ID     : {sample.sentence_id}")
print(f"  Transcript      : {sample.transcript}")
print(f"  Emotion         : {sample.emotion}")

Example Output

Loaded 936 samples

  Audio Path      : EmoTa/19_18_ang.wav
  Speaker ID      : 19
  Speaker Gender  : male
  Speaker Age     : 25
  Speaker Region  : northern
  Sentence ID     : 18
  Transcript      : நான் உன்னை சந்திக்க வேண்டும்.
  Emotion         : angry

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📄 Citation

Please cite the dataset as:

@inproceedings{thevakumar-etal-2025-emota,
  title = "{E}mo{T}a: A {T}amil Emotional Speech Dataset",
  author = "Thevakumar, Jubeerathan and Thavarasa, Luxshan and Sivatheepan, Thanikan and Kugarajah, Sajeev and Thayasivam, Uthayasanker",
  booktitle = "Proceedings of the First Workshop on Challenges in Processing South Asian Languages (CHiPSAL 2025)",
  year = "2025",
  pages = "193--201",
  address = "Abu Dhabi, UAE",
  publisher = "International Committee on Computational Linguistics"
}

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📘 License

Academic use only — see the EmoTa dataset license for details.

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[^1]: Thevakumar, J., Thavarasa, L., et al. (2025). EmoTa: A Tamil Emotional Speech Dataset. Proceedings of CHiPSAL 2025.