Meta’s AI-powered audio codec guarantees 10x compression over MP3

Final week, Meta introduced an AI-powered audio compression methodology referred to as “EnCodec” that may reportedly compress audio 10 occasions smaller than the MP3 format at 64kbps with no loss in high quality. Meta says this system might dramatically enhance the sound high quality of speech on low-bandwidth connections, resembling cellphone calls in areas with spotty service. The approach additionally works for music.

Meta debuted the expertise on October 25 in a paper titled “Excessive Constancy Neural Audio Compression,” authored by Meta AI researchers Alexandre Défossez, Jade Copet, Gabriel Synnaeve, and Yossi Adi. Meta additionally summarized the analysis on its weblog dedicated to EnCodec.

Meta describes its methodology as a three-part system skilled to compress audio to a desired goal dimension. First, the encoder transforms uncompressed knowledge right into a decrease body charge “latent area” illustration. The “quantizer” then compresses the illustration to the goal dimension whereas maintaining observe of an important data that can later be used to rebuild the unique sign. (This compressed sign is what will get despatched via a community or saved to disk.) Lastly, the decoder turns the compressed knowledge again into audio in actual time utilizing a neural community on a single CPU.

Meta’s use of discriminators proves key to creating a technique for compressing the audio as a lot as potential with out shedding key parts of a sign that make it distinctive and recognizable:

“The important thing to lossy compression is to determine adjustments that won’t be perceivable by people, as excellent reconstruction is inconceivable at low bit charges. To take action, we use discriminators to enhance the perceptual high quality of the generated samples. This creates a cat-and-mouse sport the place the discriminator’s job is to distinguish between actual samples and reconstructed samples. The compression mannequin makes an attempt to generate samples to idiot the discriminators by pushing the reconstructed samples to be extra perceptually much like the unique samples.”

It is value noting that utilizing a neural community for audio compression and decompression is way from new—particularly for speech compression—however Meta’s researchers declare they’re the primary group to use the expertise to 48 kHz stereo audio (barely higher than CD’s 44.1 kHz sampling charge), which is typical for music information distributed on the Web.

As for functions, Meta says this AI-powered “hypercompression of audio” might assist “sooner, better-quality calls” in unhealthy community situations. And, in fact, being Meta, the researchers additionally point out EnCodec’s metaverse implications, saying the expertise might finally ship “wealthy metaverse experiences with out requiring main bandwidth enhancements.”

Past that, possibly we’ll additionally get actually small music audio information out of it sometime. For now, Meta’s new tech stays within the analysis section, but it surely factors towards a future the place high-quality audio can use much less bandwidth, which might be nice information for cell broadband suppliers with overburdened networks from streaming media.