Wav2Lip
Wav2Lip is an improved version of LipGAN. It enables to Deepfake an audio within a video.
Wav2Lip is a neural network that can accurately lip-sync videos to any speech. It was developed by researchers at the Indian Institute of Technology Hyderabad and published in the journal ACM Multimedia in 2020.
Wav2Lip works by first extracting the audio track from a video and then feeding it into a neural network. The neural network then predicts the lip movements that would be associated with the audio track. These predicted lip movements are then used to create a new video that matches the audio track.
Wav2Lip has been shown to be very accurate at lip-syncing videos, even in cases where the video and audio are not perfectly aligned. It has also been shown to be able to lip-sync videos of people who were not seen during the training phase.
Wav2Lip is a powerful tool that can be used for a variety of applications, such as creating realistic deepfakes, improving the lip-syncing in videos, and generating new videos from audio tracks.
Here are some additional details about how Wav2Lip works:
The neural network that powers Wav2Lip is a generative adversarial network (GAN). GANs are a type of neural network that are trained to compete against each other. In the case of Wav2Lip, one GAN is responsible for predicting the lip movements, while the other GAN is responsible for determining whether the predicted lip movements are realistic.
Wav2Lip is trained on a large dataset of videos and audio tracks. The videos are used to train the GAN to predict lip movements, while the audio tracks are used to train the GAN to determine whether the predicted lip movements are realistic.
Wav2Lip can be used to lip-sync videos of people who were not seen during the training phase. This is because the GAN is trained to learn the general relationship between audio and lip movements, rather than the specific lip movements of individual people.
Wav2Lip is a powerful tool that has the potential to be used for a variety of applications. However, it is important to note that Wav2Lip can also be used to create realistic deepfakes. Deepfakes are videos that have been manipulated to make it appear as if someone is saying or doing something that they never actually said or did. As such, it is important to use Wav2Lip responsibly and ethically.
Make videos appear to say other things for fun creative uses. Using Wav2Lip, a pre-trained lip sync model and Python environment , you can be up an running with new lip synced creations in minutes. A very impressive deepfake audio replacement.
You can make deep fake lip sync using Python and Wav2lip ? All this technique needs is a short video and an audio speech, and the speech determines what the person on the video speaks out. Moreover the lips will be moving according to you new speech audio.
Here are some of the key features of Wav2Lip:
Can be used for lip-sync videos to any speech, regardless of the language or accent of the speaker.
Can be used to create realistic lip-synced videos for movies, TV shows, and social media posts.
Can help people with speech impairments communicate more effectively.
Wav2Lip was created at the Indian Institute of Technology Hyderabad in India. For more information on Wav2Lip, you can visit the following resources:
Wav2Lip GitHub repository: https://github.com/Rudrabha/Wav2Lip
Wav2Lip paper: https://arxiv.org/abs/2006.15985
Wav2Lip demo: https://bhaasha.iiit.ac.in/lipsync/
Google Colab Server Options:
https://colab.research.google.com/drive/1tZpDWXz49W6wDcTprANRGLo2D_EbD5J8?usp=sharing
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