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Audio-visual VAE for Speech Enhancement
https://team.inria.fr/perception/research/av-vae-se/
The results confirm that the proposed audio-visual CVAE effectively fuse audio and visual information, and it improves the speech enhancement performance compared with the audio-only VAE model, especially when the speech signal is highly corrupted by noise. We also show that the proposed unsupervised audio-visual speech enhancement approach ...
VAE for Audio-visual Speech Separation
https://team.inria.fr/perception/research/avss/
We propose an unsupervised technique based on audio-visual generative modeling of clean speech. More specifically, during training, a latent variable generative model is learned from clean speech spectrograms using a variational auto-encoder (VAE). To better utilize the visual information, the posteriors of the latent variables are inferred ...
Variational Autoencoder with CCA for Audio-Visual Cross ...
https://deepai.org/publication/variational-autoencoder-with-cca-for-audio-visual-cross-modal-retrieval
3.2.1. Encoder layers. In our VAE-CCA model, we assume that two modality data are Xv= {xiv}mi=1∈Rdv×m,Xa={xia}mi=1∈Rda×m, where m is the number of samples. dv and da are the corresponding dimensions of the visual modality and the audio modality. We set deep convolutional encoders to three layers for two modaities.
Mixture of Inference Networks for VAE-Based Audio …
https://ieeexplore.ieee.org/document/9380713
Current audio-visual VAE models do not provide an effective initialization because the two modalities are tightly coupled (concatenated) in the associated architectures. To overcome this issue, we introduce the mixture of inference networks variational autoencoder (MIN-VAE). Two encoder networks input, respectively, audio and visual data, and ...
Mixture of Inference Networks for VAE-based Audio …
https://arxiv.org/abs/1912.10647
Current audio-visual VAE models do not provide an effective initialization because the two modalities are tightly coupled (concatenated) in the associated architectures. To overcome this issue, inspired by mixture models, we introduce the mixture of inference networks variational autoencoder (MIN-VAE). Two encoder networks input, respectively ...
Mixture of Inference Networks for VAE-based Audio-visual ...
https://deepai.org/publication/mixture-of-inference-networks-for-vae-based-audio-visual-speech-enhancement
Within this model, the visual features corresponding to the lips region of the speaker are also fed to the encoder and decoder networks of the VAE. The effectiveness and superior performance of the audio-visual VAE (AV-VAE) compared to the audio-only VAE (A-VAE) for speech enhancement has been experimentally verified in [sadeghiLAGH19].
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