Overview
The EmoTa Tamil Emotional Speech Dataset is a groundbreaking collection of recordings in Sri Lankan Tamil, representing distinct dialects from the northern, eastern, western, and central provinces. It is meticulously designed for cutting-edge research in speech and emotion recognition.
Key Features
Speakers
22 native Tamil speakers with balanced gender representation (11 male, 11 female)
Emotions
Five primary emotions: Anger, Happiness, Sadness, Fear, and Neutrality
Sentences
19 carefully crafted semantically neutral sentences for unbiased emotion analysis
Quality
Professional recordings captured in controlled soundproof environment
Duration
Approximately 48 minutes of high-quality emotional speech data
Dataset Loader
Get started quickly with our Python package available on PyPI:
$ pip install emota_loader
Important Note
Make sure to clone/download the EmoTa dataset separately and point the loader to its root directory.
Sample Usage
from emota_loader import EmoTaDataset
# Point to the extracted 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 : angryDataset Structure
EmoTa/
├── happy/
├── sad/
├── angry/
├── fear/
└── neutral/
└── <spkID>_<senID>_<emo[:3]>.wavCitation
If you use EmoTa: A Tamil Emotional Speech Dataset in your research, please cite:
@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",
editor = "Sarveswaran, Kengatharaiyer and
Vaidya, Ashwini and
Krishna Bal, Bal and
Shams, Sana and
Thapa, Surendrabikram",
booktitle = "Proceedings of the First Workshop on Challenges in Processing South Asian Languages (CHiPSAL 2025)",
month = jan,
year = "2025",
address = "Abu Dhabi, UAE",
publisher = "International Committee on Computational Linguistics",
url = "https://aclanthology.org/2025.chipsal-1.19/",
pages = "193--201",
abstract = "This paper introduces EmoTa, the first emotional speech dataset in Tamil, designed to reflect the linguistic diversity of Sri Lankan Tamil speakers. EmoTa comprises 936 recorded utterances from 22 native Tamil speakers (11 male, 11 female), each articulating 19 semantically neutral sentences across five primary emotions: anger, happiness, sadness, fear, and neutrality. To ensure quality, inter-annotator agreement was assessed using Fleiss' Kappa, resulting in a substantial agreement score of 0.74. Initial evaluations using machine learning models, including XGBoost and Random Forest, yielded a high F1-score of 0.91 and 0.90 for emotion classification tasks. By releasing EmoTa, we aim to encourage further exploration of Tamil language processing and the development of innovative models for Tamil Speech Emotion Recognition."
}