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Disentangling voice and content with self-supervision for speaker recognition
For speaker recognition, it is difficult to extract an accurate speaker representation from
speech because of its mixture of speaker traits and content. This paper proposes a …
speech because of its mixture of speaker traits and content. This paper proposes a …
Speaker anonymization using orthogonal householder neural network
Speaker anonymization aims to conceal a speaker's identity while preserving content
information in speech. Current mainstream neural-network speaker anonymization systems …
information in speech. Current mainstream neural-network speaker anonymization systems …
Golden Gemini is All You Need: Finding the Sweet Spots for Speaker Verification
The residual neural networks (ResNet) demonstrate the impressive performance in
automatic speaker verification (ASV). They treat the time and frequency dimensions equally …
automatic speaker verification (ASV). They treat the time and frequency dimensions equally …
Language-independent speaker anonymization approach using self-supervised pre-trained models
Speaker anonymization aims to protect the privacy of speakers while preserving spoken
linguistic information from speech. Current mainstream neural network speaker …
linguistic information from speech. Current mainstream neural network speaker …
Multi-level attention network: Mixed time–frequency channel attention and multi-scale self-attentive standard deviation pooling for speaker recognition
In this paper, we propose a more efficient lightweight speaker recognition network, the multi-
level attention network (MANet). MANet aims to generate more robust and discriminative …
level attention network (MANet). MANet aims to generate more robust and discriminative …
RSKNet-MTSP: Effective and portable deep architecture for speaker verification
Y Wu, C Guo, J Zhao, X **, J Xu - Neurocomputing, 2022 - Elsevier
The convolutional neural network (CNN) based approaches have shown great success for
speaker verification (SV) tasks, where modeling long temporal context and reducing …
speaker verification (SV) tasks, where modeling long temporal context and reducing …
Adapting General Disentanglement-Based Speaker Anonymization for Enhanced Emotion Preservation
A general disentanglement-based speaker anonymization system typically separates
speech into content, speaker, and prosody features using individual encoders. This paper …
speech into content, speaker, and prosody features using individual encoders. This paper …
ResSKNet-SSDP: effective and light end-to-end architecture for speaker recognition
In speaker recognition tasks, convolutional neural network (CNN)-based approaches have
shown significant success. Modeling the long-term contexts and efficiently aggregating the …
shown significant success. Modeling the long-term contexts and efficiently aggregating the …
[HTML][HTML] Explore long-range context features for speaker verification
Multi-scale context information, especially long-range dependency, has shown to be
beneficial for speaker verification (SV) tasks. In this paper, we propose three methods to …
beneficial for speaker verification (SV) tasks. In this paper, we propose three methods to …
Multimodal modeling for spoken language identification
Spoken language identification refers to the task of automatically predicting the spoken
language in a given utterance. Conventionally, it is modeled as a speech-based language …
language in a given utterance. Conventionally, it is modeled as a speech-based language …