1 citations · 1 across the 6 of their papers we have counts for
6 papers
Foundation Model Hidden Representations for Heart Rate Estimation from Auscultation
Jingping Nie, Dung T. Tran, Karan Thakkar +5
Auscultation, particularly heart sound, is a non-invasive technique that provides essential vital sign information. Recently, self-supervised acoustic representation foundation mod…
Voice Quality Dimensions as Interpretable Primitives for Speaking Style for Atypical Speech and Affect
Jaya Narain, Vasudha Kowtha, Colin Lea +8
Perceptual voice quality dimensions describe key characteristics of atypical speech and other speech modulations. Here we develop and evaluate voice quality models for seven voice…
Learning to Detect Novel and Fine-Grained Acoustic Sequences Using Pretrained Audio Representations
Vasudha Kowtha, Miquel Espi Marques, Jonathan Huang +2
This work investigates pretrained audio representations for few shot Sound Event Detection. We specifically address the task of few shot detection of novel acoustic sequences, or s…
Pre-trained Model Representations and their Robustness against Noise for Speech Emotion Analysis
Vikramjit Mitra, Vasudha Kowtha, Hsiang-Yun Sherry Chien +2
Pre-trained model representations have demonstrated state-of-the-art performance in speech recognition, natural language processing, and other applications. Speech models, such as…
Speech Emotion: Investigating Model Representations, Multi-Task Learning and Knowledge Distillation
Vikramjit Mitra, Hsiang-Yun Sherry Chien, Vasudha Kowtha +2
Estimating dimensional emotions, such as activation, valence and dominance, from acoustic speech signals has been widely explored over the past few years. While accurate estimation…
Detecting Emotion Primitives from Speech and their use in discerning Categorical Emotions
Vasudha Kowtha, Vikramjit Mitra, Chris Bartels +5
Emotion plays an essential role in human-to-human communication, enabling us to convey feelings such as happiness, frustration, and sincerity. While modern speech technologies rely…