Speech and speaker recognition systems are employed in a variety of applications, from
personal assistants to telephony surveillance and biometric authentication. The wide …

We present a structured overview of adaptation algorithms for neural network-based speech
recognition, considering both hybrid hidden Markov model/neural network systems and end …

Despite rapid progress in the recent past, current speech recognition systems still require
labeled training data which limits this technology to a small fraction of the languages spoken …

We construct targeted audio adversarial examples on automatic speech recognition. Given
any audio waveform, we can produce another that is over 99.9% similar, but transcribes as …

Unconstrained text recognition is an important computer vision task, featuring a wide variety
of different sub-tasks, each with its own set of challenges. One of the biggest promises of …

This paper proposes LPRNet-end-to-end method for Automatic License Plate Recognition
without preliminary character segmentation. Our approach is inspired by recent …

This paper presents Metamorph, a system that generates imperceptible audio that can
survive over-the-air trans-mission to attack the neural network of a speech recognition …

In this paper, we propose SpecPatch, a human-in-the loop adversarial audio attack on
automated speech recognition (ASR) systems. Existing audio adversarial attacker assumes …

Abstract Sign Language Translation (SLT) is a challenging task that aims to translate sign
videos into spoken language. Inspired by the strong translation capabilities of large …

Automatic speech transcription and speaker recognition are usually treated as separate
tasks even though they are interdependent. In this study, we investigate training a single …