Speaker recognition based on deep learning: An overview
Speaker recognition is a task of identifying persons from their voices. Recently, deep
learning has dramatically revolutionized speaker recognition. However, there is lack of …
learning has dramatically revolutionized speaker recognition. However, there is lack of …
Adversarial attack and defense strategies for deep speaker recognition systems
Robust speaker recognition, including in the presence of malicious attacks, is becoming
increasingly important and essential, especially due to the proliferation of smart speakers …
increasingly important and essential, especially due to the proliferation of smart speakers …
Individual identification in acoustic recordings
Recent advances in bioacoustics combined with acoustic individual identification (AIID)
could open frontiers for ecological and evolutionary research because traditional methods of …
could open frontiers for ecological and evolutionary research because traditional methods of …
Neural mos prediction for synthesized speech using multi-task learning with spoofing detection and spoofing type classification
Several studies have proposed deep-learning-based models to predict the mean opinion
score (MOS) of synthesized speech, showing the possibility of replacing human raters …
score (MOS) of synthesized speech, showing the possibility of replacing human raters …
Robust multi-channel far-field speaker verification under different in-domain data availability scenarios
The popularity and application of smart home devices have made far-field speaker
verification an urgent need. However, speaker verification performance is unsatisfactory …
verification an urgent need. However, speaker verification performance is unsatisfactory …
Adversarial defense for deep speaker recognition using hybrid adversarial training
Deep neural network based speaker recognition systems can easily be deceived by an
adversary using minuscule imperceptible perturbations to the input speech samples. These …
adversary using minuscule imperceptible perturbations to the input speech samples. These …
Robust speaker recognition using unsupervised adversarial invariance
In this paper, we address the problem of speaker recognition in challenging acoustic
conditions using a novel method to extract robust speaker-discriminative speech …
conditions using a novel method to extract robust speaker-discriminative speech …
Meta-learning with latent space clustering in generative adversarial network for speaker diarization
The performance of most speaker diarization systems with x-vector embeddings is both
vulnerable to noisy environments and lacks domain robustness. Earlier work on speaker …
vulnerable to noisy environments and lacks domain robustness. Earlier work on speaker …
Temporal dynamics of workplace acoustic scenes: Egocentric analysis and prediction
Identification of the acoustic environment from an audio recording, also known as acoustic
scene classification, is an active area of research. In this paper, we study dynamically …
scene classification, is an active area of research. In this paper, we study dynamically …
[PDF][PDF] Deep speaker embedding with frame-constrained training strategy for speaker verification.
B Gu - INTERSPEECH, 2022 - isca-archive.org
Speech signals contain a lot of side information (content, stress, etc.), besides the voiceprint
statistics. The session-variablility poses a huge challenge for modeling speaker …
statistics. The session-variablility poses a huge challenge for modeling speaker …