Apr 7, 2020 · We find that the speaker recognition system is also vulnerable to the attack, and we achieve a high success rate on the non-targeted attack.

In this work, we focus on attacking the speaker recognition and present a model as well as its optimization method to attack the well-trained state-of-the-art ...

Nov 15, 2021 · A lightweight multi-layer convolutional neural network to fool the well-trained state-of-the-art speaker recognition model by adding imperceptible ...

We proposed a lightweight model to attack the speaker recognition model, and we find that the speaker recognition model is vulnerable to the attack.

A lightweight model is presented, a lightweight model to fool the deep speaker recognition model by adding imperceptible perturbations onto the raw speech ...

Sep 10, 2024 · We find that the speaker recognition system is also vulnerable to the attack, and we achieve a high success rate on the non-targeted attack.

code for paper "learning to fool the speaker recognition" - learning-to-fool-the-speaker-recognition/prepare_dataset.py at master ...

In particular, by adding a well-crafted inconspicuous noise to the original audio, our attack can fool the speaker recognition system to make false predictions.

To improve the performance, speech recognition will minimize speaker-dependent variations to determine the underlying text or command, whereas speaker.

Apr 30, 2022 · Universality: it is the ability of an adversarial perturbation to fool a given model on any clean samples with high probability. If an adversary ...