Papers
SpeechMLC: Speech Multi-label Classification
Miseul Kim, Seyun Um, Hyeonjin Cha et al.
Attention Is Not Always the Answer: Optimizing Voice Activity Detection with Simple Feature Fusion
Kumud Tripathi, Chowdam Venkata Kumar, Pankaj Wasnik
Can Speech Accurately Detect Depression in Patients With Comorbid Dementia? An Approach for Mitigating Confounding Effects of Depression and Dementia
Sophie Young, Fuxiang Tao, Bahman Mirheidari et al.
Towards the Objective Characterisation of Major Depressive Disorder Using Speech Data from a 12-week Observational Study with Daily Measurements
Robert Lewis, Szymon Fedor, Nelson Hidalgo Julia et al.
Zero-Shot Speech-Based Depression and Anxiety Assessment with LLMs
Erfan Loweimi, Sofia de la Fuente Garcia, Saturnino Luz
Leveraging Ordinal Information for Speech-based Depression Classification
Lishi Zuo, Man-Wai Mak
Test-Time Training for Speech-based Depression Detection
Sri Harsha Dumpala, Chandramouli S. Sastry, Rudolf Uher et al.
Explainable Depression Detection using Masked Hard Instance Mining
Patawee Prakrankamanant, Shinji Watanabe, Ekapol Chuangsuwanich
Emotion-Guided Graph Attention Networks for Speech-Based Depression Detection under Emotion-Inducting Tasks
Yuqiu Zhou, Yongjie Zhou, Yudong Yang et al.
DepressGEN: Synthetic Data Generation Framework for Depression Detection
Wenrui Liang, Rong Zhang, Xuezhen Zhang et al.
Speech Reference Intervals: An Assessment of Feasibility in Depression Symptom Severity Prediction
Lauren White, Ewan Carr, Judith Dineley et al.
Synthetic Data Generation for Phrase Break Prediction with Large Language Model
Hoyeon Lee, Sejung Son, Ye-Eun Kang et al.
ExagTTS: An Approach Towards Controllable Word Stress Incorporated TTS for Exaggerated Synthesized Speech Aiding Second Language Learners
Anindita Mondal, Monica Surtani, Anil Kumar Vuppala et al.
GST-BERT-TTS: Prosody Prediction Without Accentual Labels For Multi-Speaker TTS Using BERT With Global Style Tokens
Tadashi Ogura, Takuma Okamoto, Yamato Ohtani et al.
Investigating Stochastic Methods for Prosody Modeling in Speech Synthesis
Paul Mayer, Florian Lux, Alejandro Pérez-González-de-Martos et al.
Counterfactual Activation Editing for Post-hoc Prosody and Mispronunciation Correction in TTS Models
Kyowoon Lee, Artyom Stitsyuk, Gunu Jho et al.
ProMode: A Speech Prosody Model Conditioned on Acoustic and Textual Inputs
Eray Eren, Qingju Liu, Hyeongwoo Kim et al.
Network of acoustic characteristics for the automatic detection of suicide risk from speech. Contribution to the 2025 SpeechWellness challenge by the Semawave team
Vincent P. Martin, Charles Brazier, Maxime Amblard et al.
Language-Agnostic Suicidal Risk Detection Using Large Language Models
June-Woo Kim, Wonkyo Oh, Haram Yoon et al.
In-context learning capabilities of Large Language Models to detect suicide risk among adolescents from speech transcripts
Filomene Roquefort, Alexandre Ducorroy, Rachid Riad
Predicting Adolescent Suicidal Risk from Multi-task-based Speech: An Ensemble Learning Approach
Xi Chen, Renzhe Yu, Yanshen Tan et al.
Leveraging Large Language Models for Spontaneous Speech-Based Suicide Risk Detection
Yifan Gao, Jiao Fu, Long Guo et al.
The 1st SpeechWellness Challenge: Detecting Suicide Risk Among Adolescents
Wen Wu, Ziyun Cui, Chang Lei et al.
Leveraging Text and Speech Processing for Suicide Risk Classification in Chinese Adolescents
Justyna Krzywdziak, Bartłomiej Eljasiak, Joanna Stępień et al.