1 citations · 4 across the 26 of their papers we have counts for
8 papers · 2 filters
Investigating Prosodic Signatures via Speech Pre-Trained Models for Audio Deepfake Source Attribution
Orchid Chetia Phukan, Drishti Singh, Swarup Ranjan Behera +2
In this work, we investigate various state-of-the-art (SOTA) speech pre-trained models (PTMs) for their capability to capture prosodic signatures of the generative sources for audi…
Multi-View Multi-Task Modeling with Speech Foundation Models for Speech Forensic Tasks
Orchid Chetia Phukan, Devyani Koshal, Swarup Ranjan Behera +2
Speech forensic tasks (SFTs), such as automatic speaker recognition (ASR), speech emotion recognition (SER), gender recognition (GR), and age estimation (AE), find use in different…
Beyond Speech and More: Investigating the Emergent Ability of Speech Foundation Models for Classifying Physiological Time-Series Signals
Orchid Chetia Phukan, Swarup Ranjan Behera, Girish +3
Despite being trained exclusively on speech data, speech foundation models (SFMs) like Whisper have shown impressive performance in non-speech tasks such as audio classification. T…
SeQuiFi: Mitigating Catastrophic Forgetting in Speech Emotion Recognition with Sequential Class-Finetuning
Sarthak Jain, Orchid Chetia Phukan, Swarup Ranjan Behera +2
In this work, we introduce SeQuiFi, a novel approach for mitigating catastrophic forgetting (CF) in speech emotion recognition (SER). SeQuiFi adopts a sequential class-finetuning s…
Representation Loss Minimization with Randomized Selection Strategy for Efficient Environmental Fake Audio Detection
Orchid Chetia Phukan, Girish, Mohd Mujtaba Akhtar +5
The adaptation of foundation models has significantly advanced environmental audio deepfake detection (EADD), a rapidly growing area of research. These models are typically fine-tu…
Avengers Assemble: Amalgamation of Non-Semantic Features for Depression Detection
Orchid Chetia Phukan, Swarup Ranjan Behera, Shubham Singh +5
In this study, we address the challenge of depression detection from speech, focusing on the potential of non-semantic features (NSFs) to capture subtle markers of depression. Whil…
Strong Alone, Stronger Together: Synergizing Modality-Binding Foundation Models with Optimal Transport for Non-Verbal Emotion Recognition
Orchid Chetia Phukan, Mohd Mujtaba Akhtar, Girish +5
In this study, we investigate multimodal foundation models (MFMs) for emotion recognition from non-verbal sounds. We hypothesize that MFMs, with their joint pre-training across mul…
Are Music Foundation Models Better at Singing Voice Deepfake Detection? Far-Better Fuse them with Speech Foundation Models
Orchid Chetia Phukan, Sarthak Jain, Swarup Ranjan Behera +3
In this study, for the first time, we extensively investigate whether music foundation models (MFMs) or speech foundation models (SFMs) work better for singing voice deepfake detec…