88 citations · 204 across the 28 of their papers we have counts for
16 papers · 1 filter
Describing emotions with acoustic property prompts for speech emotion recognition
Hira Dhamyal, Benjamin Elizalde, Soham Deshmukh +3
Emotions lie on a broad continuum and treating emotions as a discrete number of classes limits the ability of a model to capture the nuances in the continuum. The challenge is how…
Unifying the Discrete and Continuous Emotion labels for Speech Emotion Recognition
Roshan Sharma, Hira Dhamyal, Bhiksha Raj +1
Traditionally, in paralinguistic analysis for emotion detection from speech, emotions have been identified with discrete or dimensional (continuous-valued) labels. Accordingly, mod…
Ontological Learning from Weak Labels
Larry Tang, Po Hao Chou, Yi Yu Zheng +3
Ontologies encompass a formal representation of knowledge through the definition of concepts or properties of a domain, and the relationships between those concepts. In this work,…
Identifying Actions for Sound Event Classification
Benjamin Elizalde, Radu Revutchi, Samarjit Das +3
In Psychology, actions are paramount for humans to identify sound events. In Machine Learning (ML), action recognition achieves high accuracy; however, it has not been asked whethe…
Detection and Evaluation of human and machine generated speech in spoofing attacks on automatic speaker verification systems
Yang Gao, Jiachen Lian, Bhiksha Raj +1
Automatic speaker verification (ASV) systems utilize the biometric information in human speech to verify the speaker's identity. The techniques used for performing speaker verifica…
FoolHD: Fooling speaker identification by Highly imperceptible adversarial Disturbances
Ali Shahin Shamsabadi, Francisco Sepúlveda Teixeira, Alberto Abad +3
Speaker identification models are vulnerable to carefully designed adversarial perturbations of their input signals that induce misclassification. In this work, we propose a white-…