Papers
PhonemeFake: Redefining Deepfake Realism with Language-Driven Segmental Manipulation and Adaptive Bilevel Detection
Oguzhan Baser, Ahmet Ege Tanriverdi, Sriram Vishwanath et al.
A Comparative Study on Proactive and Passive Detection of Deepfake Speech
Chia-Hua Wu, Wanying Ge, Xin Wang et al.
Leveraging SSL Speech Features and Mamba for Enhanced DeepFake Detection
Hoan My Tran, Damien Lolive, David Guennec et al.
Naturalness-Aware Curriculum Learning with Dynamic Temperature for Speech Deepfake Detection
Taewoo Kim, Guisik Kim, Choongsang Cho et al.
Multimodal Speech-Based Biomarkers Outperform the ALS Functional Rating Scale in Predicting Individual Disease Progression in ALS
Hardik Kothare, Michael Neumann, Vikram Ramanarayanan
Influence of Room Acoustics on Objective Voice Assessment Methods in the Context of Speech and Language Therapy
Sven Franz, Tanja Grewe, Bernd T. Meyer et al.
Speech-Based Automatic Chronic Kidney Disease Diagnosis via Transformer Fusion of Glottal and Spectrogram Features
Jihyun Mun, Minhwa Chung, Sunhee Kim
Stuttering Detection Based on Self-Attention Weights of Temporal Acoustic Vector Sequence
Genzo Miyahara, Tsuneo Kato, Akihiro Tamura
Towards Classification of Typical and Atypical Disfluencies: A Self Supervised Representation Approach
Priyanka Kommagouni, Pragya Khanna, Vamshiraghusimha Narasinga et al.
Automatic Detection and Sub-typing of Primary Progressive Aphasia from Speech: Integrating Task-Specific Features and Spatio-Semantic Graphs
Fritz Peters, W Richard Bevan-Jones, Grace Threlfall et al.
Synchronous analysis of abnormal acoustic and linguistic production in Parkinson's speech
Daniel Escobar-Grisales, Cristian David Ríos-Urrego, Sabato Marco Siniscalchi et al.
Speech power spectra: a window into neural oscillations in Parkinson's disease
Sevada Hovsepyan, Mathew Magimai Doss
On the Relevance of Clinical Assessment Tasks for the Automatic Detection of Parkinson’s Disease Medication State from Speech
David Gimeno-Gómez, Rubén Solera-Ureña, Anna Pompili et al.
M3L: A Multi-Modal and Multi-Lingual Depression Detection Framework
Jiajun You, Shuai Wang, Xun Gong et al.
Identifying Vocal and Facial Biomarkers of Depression in Large-Scale Remote Recordings: A Multimodal Study Using Mixed-Effects Modeling
Nelson Hidalgo Julia, Robert Lewis, Craig Ferguson et al.
A Study on The Impact of Foundation Models on Automatic Depression Detection from Speech Signals
Bubai Maji, Monorama Swain, Shazia Nasreen et al.
Speech and Text Foundation Models for Depression Detection: Cross-Task and Cross-Language Evaluation
Lucía Gómez-Zaragozá, Javier Marín-Morales, Mariano Alcañiz et al.
An interpretable speech foundation model for depression detection by revealing prediction-relevant acoustic features from long speech
Qingkun Deng, Saturnino Luz, Sofia de la Fuente Garcia
A Hybrid Approach to Combining Role Diarization with ASR for Professional Conversations
Bongjun Kim, Arindam Ghosh, Mark C. Fuhs et al.
Streaming Sortformer: Speaker Cache-Based Online Speaker Diarization with Arrival-Time Ordering
Ivan Medennikov, Taejin Park, Weiqing Wang et al.
Diarization-Guided Multi-Speaker Embeddings
Joonas Kalda, Clément Pagés, Tanel Alumäe et al.
Selective Channel Attention based Target Speaker Voice Activity Detection for Speaker Diarization under AD-HOC Microphone Array Settings
Hongyu Zhang, Ming Cheng, Jing Feng et al.
Spatio-Spectral Diarization of Meetings by Combining TDOA-based Segmentation and Speaker Embedding-based Clustering
Tobias Cord-Landwehr, Tobias Gburrek, Marc Deegen et al.
Pushing the Limits of End-to-End Diarization
Samuel J. Broughton, Lahiru Samarakoon