@inproceedings{g-etal-2026-shared,
title = "Shared Task on Depression Detection from {M}alayalam and {T}amil Speech Data",
author = "G, Jyothish Lal and
B, Premjith and
Chakravarthi, Bharathi Raja and
Rajiakodi, Saranya and
Durairaj, Thenmozhi and
Kumaresan, Prasanna Kumar",
editor = "Chakravarthi, Bharathi Raja and
Priyadharshini, Ruba and
Madasamy, Anand Kumar and
Thavareesan, Sajeetha and
Rajiakodi, Saranya and
Navaneethakrishnan, Subalalitha and
Chinnappa, Dhivya and
Palani, Balasubramanian and
Subramanian, Malliga and
Shanmugavadivel, Kogilavani and
Rajalakshmi, Ratnavel",
booktitle = "Proceedings of the Sixth Workshop on Speech, Vision, and Language Technologies for {D}ravidian Languages",
month = jul,
year = "2026",
address = "Underline (Virtual)",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2026.dravidianlangtech-1.13/",
pages = "114--123",
ISBN = "979-8-89176-401-9",
abstract = "Depression is one of the most common mental health problems in the world. It affects a person{'}s emotions, thinking, energy levels, and daily life. Early detection of depression is very important to provide timely support and treatment. While many studies focus on identifying depression from text, speech also carries important emotional and psychological signals that are often not fully explored. This paper presents an overview of the shared task on Depression Detection in Dravidian Languages (DD- DL). The task focuses on identifying signs of depression from speech data in two low-resource Dravidian languages: Tamil and Malayalam. Participants were provided with curated training datasets and were asked to build systems to classify speech samples as Depressed or Non-Depressed. The shared task includes two subtasks: (1) Depression detection in Tamil and (2) Depression detection in Malayalam. Participants applied various machine learning and deep learning approaches to model the acoustic and linguistic characteristics of speech. All submissions were evaluated using the macro-F1 score, which ensures fair performance measurement across classes."
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%0 Conference Proceedings
%T Shared Task on Depression Detection from Malayalam and Tamil Speech Data
%A G, Jyothish Lal
%A B, Premjith
%A Chakravarthi, Bharathi Raja
%A Rajiakodi, Saranya
%A Durairaj, Thenmozhi
%A Kumaresan, Prasanna Kumar
%Y Chakravarthi, Bharathi Raja
%Y Priyadharshini, Ruba
%Y Madasamy, Anand Kumar
%Y Thavareesan, Sajeetha
%Y Rajiakodi, Saranya
%Y Navaneethakrishnan, Subalalitha
%Y Chinnappa, Dhivya
%Y Palani, Balasubramanian
%Y Subramanian, Malliga
%Y Shanmugavadivel, Kogilavani
%Y Rajalakshmi, Ratnavel
%S Proceedings of the Sixth Workshop on Speech, Vision, and Language Technologies for Dravidian Languages
%D 2026
%8 July
%I Association for Computational Linguistics
%C Underline (Virtual)
%@ 979-8-89176-401-9
%F g-etal-2026-shared
%X Depression is one of the most common mental health problems in the world. It affects a person’s emotions, thinking, energy levels, and daily life. Early detection of depression is very important to provide timely support and treatment. While many studies focus on identifying depression from text, speech also carries important emotional and psychological signals that are often not fully explored. This paper presents an overview of the shared task on Depression Detection in Dravidian Languages (DD- DL). The task focuses on identifying signs of depression from speech data in two low-resource Dravidian languages: Tamil and Malayalam. Participants were provided with curated training datasets and were asked to build systems to classify speech samples as Depressed or Non-Depressed. The shared task includes two subtasks: (1) Depression detection in Tamil and (2) Depression detection in Malayalam. Participants applied various machine learning and deep learning approaches to model the acoustic and linguistic characteristics of speech. All submissions were evaluated using the macro-F1 score, which ensures fair performance measurement across classes.
%U https://aclanthology.org/2026.dravidianlangtech-1.13/
%P 114-123
Markdown (Informal)
[Shared Task on Depression Detection from Malayalam and Tamil Speech Data](https://aclanthology.org/2026.dravidianlangtech-1.13/) (G et al., DravidianLangTech 2026)
ACL
- Jyothish Lal G, Premjith B, Bharathi Raja Chakravarthi, Saranya Rajiakodi, Thenmozhi Durairaj, and Prasanna Kumar Kumaresan. 2026. Shared Task on Depression Detection from Malayalam and Tamil Speech Data. In Proceedings of the Sixth Workshop on Speech, Vision, and Language Technologies for Dravidian Languages, pages 114–123, Underline (Virtual). Association for Computational Linguistics.