Last week, Meta announced an AI-powered audio compression method called “EnCodec” that can reportedly compress audio 10 times smaller than the MP3 format at 64kbps with no loss in quality. Meta says this technique could dramatically improve the sound quality of speech on low-bandwidth connections, such as phone calls in areas with spotty service. The technique also works for music.
Meta debuted the technology on October 25 in a paper titled “High Fidelity Neural Audio Compression,” authored by Meta AI researchers Alexandre Défossez, Jade Copet, Gabriel Synnaeve, and Yossi Adi. Meta also summarized the research on its blog devoted to EnCodec.
Meta describes its method as a three-part system trained to compress audio to a desired target size. First, the encoder transforms uncompressed data into a lower frame rate “latent space” representation. The “quantizer” then compresses the representation to the target size while keeping track of the most important information that will later be used to rebuild the original signal. (This compressed signal is what gets sent through a network or saved to disk.) Finally, the decoder turns the compressed data back into audio in real time using a neural network on a single CPU.