Model Card for EnCodec This model card provides details and information about EnCodec, a state of the art real time audio codec developed by Meta AI. Model Details Model Description EnCodec is a high fidelity audio codec leveraging neural networks. It introduces a streaming encoder decoder architecture with quantized latent space, trained in an end to end fashion. The model simplifies and speeds up training using a single multiscale spectrogram adversary that efficiently reduces artifacts and produces high quality samples. It also includes a novel loss balancer mechanism that stabilizes training by decoupling the choice of hyperparameters from the typical scale of the loss. Additionally, lightweight Transformer models are used to further compress the obtained representation while maintaining real time performance. Developed by: Meta AI Model type: Audio Codec Model Sources Repository: GitHub Repository Paper: EnCodec: End to End Neural Audio Codec Uses Direct Use EnCodec can be used directly as an audio codec for real time compression and decompression of audio signals. It provides high quality audio compression and efficient decoding. The model was trained on various bandwiths, wh…
We use cookies for essential functionality and analytics. You can accept or reject analytics cookies.Cookie policy