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Found 10 papers, 6 papers with code
Improving Generalization Ability of Countermeasures for New Mismatch Scenario by Combining Multiple Advanced Regularization Terms
The ability of countermeasure models to generalize from seen speech synthesis methods to unseen ones has been investigated in the ASVspoof challenge.
Beyond Universal Transformer: block reusing with adaptor in Transformer for automatic speech recognition
To overcome the drawback of universal Transformer models for the application of ASR on edge devices, we propose a solution that can reuse the block in Transformer models for the occasion of the small footprint ASR system, which meets the objective of accommodating resource limitations without compromising recognition accuracy.
Ranked #11 on
Speech Recognition
on AISHELL-1
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+1
Cross-modal Audio-visual Co-learning for Text-independent Speaker Verification
Visual speech (i. e., lip motion) is highly related to auditory speech due to the co-occurrence and synchronization in speech production.
Xiaoicesing 2: A High-Fidelity Singing Voice Synthesizer Based on Generative Adversarial Network
XiaoiceSing is a singing voice synthesis (SVS) system that aims at generating 48kHz singing voices.
HiFi-WaveGAN: Generative Adversarial Network with Auxiliary Spectrogram-Phase Loss for High-Fidelity Singing Voice Generation
Entertainment-oriented singing voice synthesis (SVS) requires a vocoder to generate high-fidelity (e. g. 48kHz) audio.
Deep Spectro-temporal Artifacts for Detecting Synthesized Speech
The Audio Deep Synthesis Detection (ADD) Challenge has been held to detect generated human-like speech.
Joint Speaker Encoder and Neural Back-end Model for Fully End-to-End Automatic Speaker Verification with Multiple Enrollment Utterances
Conventional automatic speaker verification systems can usually be decomposed into a front-end model such as time delay neural network (TDNN) for extracting speaker embeddings and a back-end model such as statistics-based probabilistic linear discriminant analysis (PLDA) or neural network-based neural PLDA (NPLDA) for similarity scoring.
Spoofing-Aware Attention based ASV Back-end with Multiple Enrollment Utterances and a Sampling Strategy for the SASV Challenge 2022
Current state-of-the-art automatic speaker verification (ASV) systems are vulnerable to presentation attacks, and several countermeasures (CMs), which distinguish bona fide trials from spoofing ones, have been explored to protect ASV.
Exploring Deep Learning for Joint Audio-Visual Lip Biometrics
Audio-visual (AV) lip biometrics is a promising authentication technique that leverages the benefits of both the audio and visual modalities in speech communication.
Attention Back-end for Automatic Speaker Verification with Multiple Enrollment Utterances
Probabilistic linear discriminant analysis (PLDA) or cosine similarity have been widely used in traditional speaker verification systems as back-end techniques to measure pairwise similarities.
Ranked #1 on
Speaker Verification
on CN-CELEB
