90 citations · 178 across the 45 of their papers we have counts for
8 papers · 1 filter
Unsupervised Speech Segmentation and Variable Rate Representation Learning using Segmental Contrastive Predictive Coding
Saurabhchand Bhati, Jesús Villalba, Piotr Żelasko +2
Typically, unsupervised segmentation of speech into the phone and word-like units are treated as separate tasks and are often done via different methods which do not fully leverage…
The JHU submission to VoxSRC-21: Track 3
Jejin Cho, Jesus Villalba, Najim Dehak
This technical report describes Johns Hopkins University speaker recognition system submitted to Voxceleb Speaker Recognition Challenge 2021 Track 3: Self-supervised speaker verifi…
Beyond Isolated Utterances: Conversational Emotion Recognition
Raghavendra Pappagari, Piotr Żelasko, Jesús Villalba +2
Speech emotion recognition is the task of recognizing the speaker's emotional state given a recording of their utterance. While most of the current approaches focus on inferring em…
Representation Learning to Classify and Detect Adversarial Attacks against Speaker and Speech Recognition Systems
Jesús Villalba, Sonal Joshi, Piotr Żelasko +1
Adversarial attacks have become a major threat for machine learning applications. There is a growing interest in studying these attacks in the audio domain, e.g, speech and speaker…
Segmental Contrastive Predictive Coding for Unsupervised Word Segmentation
Saurabhchand Bhati, Jesús Villalba, Piotr Żelasko +2
Automatic detection of phoneme or word-like units is one of the core objectives in zero-resource speech processing. Recent attempts employ self-supervised training methods, such as…
Deep Feature CycleGANs: Speaker Identity Preserving Non-parallel Microphone-Telephone Domain Adaptation for Speaker Verification
Saurabh Kataria, Jesús Villalba, Piotr Żelasko +2
With the increase in the availability of speech from varied domains, it is imperative to use such out-of-domain data to improve existing speech systems. Domain adaptation is a prom…
Adversarial Attacks and Defenses for Speech Recognition Systems
Piotr Żelasko, Sonal Joshi, Yiwen Shao +4
The ubiquitous presence of machine learning systems in our lives necessitates research into their vulnerabilities and appropriate countermeasures. In particular, we investigate the…
Study of Pre-processing Defenses against Adversarial Attacks on State-of-the-art Speaker Recognition Systems
Sonal Joshi, Jesús Villalba, Piotr Żelasko +2
Adversarial examples to speaker recognition (SR) systems are generated by adding a carefully crafted noise to the speech signal to make the system fail while being imperceptible to…