Why xHE-AAC is being embraced at Meta

• We’re sharing how Meta delivers high-quality audio at scale with the xHE-AAC audio codec.
• xHE-AAC has already been deployed on Fb and Instagram to offer enhanced audio for options like Reels and Tales. 

At Meta, we serve each media use case conceivable for billions of individuals internationally — from short-form, user-generated content material, resembling Reels, to premium video on demand (VOD) and dwell broadcasts. Given this, we want a next-generation audio codec that helps a spread of working factors with glorious compression effectivity and trendy, system-level audio options. 

To deal with these wants now and into the longer term, Meta has embraced xHE-AAC because the automobile for delivering high-quality audio at scale.

The advantages of xHE-AAC

xHE-AAC is the most recent member of the MPEG AAC audio codec household. The Fraunhofer Institute for Integrated Circuits IIS performed a considerable function within the growth of xHE-AAC and the MPEG-D DRC commonplace.

Right now, xHE-AAC is already offering a superior audio expertise on Fb and Instagram — together with on Reels and Tales — and has a lot of useful options.

Loudness administration

With a whole bunch of thousands and thousands of uploads per day throughout Fb and Instagram, we obtain audio tracks with loudness ranges starting from silence to full scale, and every little thing in between. 

When individuals play these movies sequentially, they will understand some audio as being too loud or too quiet. This creates listener fatigue from having to continually modify the quantity.

xHE-AAC’s built-in loudness administration system solves for loudness inconsistency whereas meticulously preserving creator intent by bringing the common loudness of all classes to the identical goal degree and managing the dynamic vary of every session to suit the playback setting.

As a substitute of burning in a selected goal degree and dynamic vary compression (DRC) profile throughout encoding, xHE-AAC permits us to depart the unique audio traits untouched and delegate loudness administration processing to the shopper through loudness metadata, for the optimum audio expertise primarily based on context. 

Because of xHE-AAC’s loudness administration, individuals can spend extra time immersed of their favourite content material and fewer time twiddling with the quantity management.

Adaptive bit price audio

Most individuals who use our apps devour media on cell gadgets and anticipate the best audio high quality with out interruption. This presents a problem for streaming media as a result of connection high quality varies on cell and may end up in a really uneven person expertise. 

To optimize high quality underneath dynamic bandwidth constraints, we produce a number of video and audio qualities to match various community situations at playback time. Despite the fact that we produce a number of audio lanes, we’ve got traditionally solely employed adaptive bit price (ABR) algorithms to modify video qualities throughout playback as a result of it’s tough to allow adaptive bit price audio with out compromising high quality throughout lane transitions.

With the intention to allow seamless audio ABR, xHE-AAC introduces the idea of speedy playout frames (IPFs) that include all the info essential to begin enjoying a brand new audio lane with out counting on knowledge from different frames. By inserting an IPF at the start of every Dynamic Adaptive Streaming over HTTP (DASH) phase and aligning the phase durations of every lane, we will seamlessly swap between audio lanes throughout playback to offer the highest-quality audio at any obtainable bandwidth whereas avoiding playback stalls.

After launching audio ABR on Fb for Android, we had been capable of enhance person expertise by lowering the variety of classes the place playback stalls. 

How we deployed xHE-AAC

We generate xHE-AAC bitstreams utilizing an encoder SDK supplied by the Fraunhofer Institute for Built-in Circuits IIS, after which put together the ensuing audio recordsdata for DASH streaming with shaka-packager. The xHE-AAC encoder’s two-pass encoding mode is used to measure the enter loudness envelope and common program loudness on the primary move and carry out the precise audio knowledge compression on the second move. As an additional benefit, two-pass encoding permits us to make use of loudness vary management (LRAC) DRC, which mitigates pumping artifacts in any other case launched by single-pass DRC algorithms.

To organize an xHE-AAC audio adaptation set for ABR supply, IPFs are inserted at fixed time intervals, audio configuration parameters resembling pattern price and channel configuration are saved fixed, and distinctive stream identifiers are chosen for every lane within the audio adaptation set.

At playback time, we custom-fit the audio to the listening setting by configuring a goal loudness degree and DRC impact kind primarily based on context, and due to the embedded loudness metadata, we will adapt a single xHE-AAC bitstream to quite a lot of audio consumption use instances, from headphones to gadget audio system and numerous ranges of background noise. Lastly, if the shopper is starved for knowledge or bandwidth is plentiful, audio ABR will robotically swap audio qualities to make sure that the best audio high quality is performed with out interrupting the playback session.

The place are you able to expertise xHE-AAC right now?

You possibly can expertise xHE-AAC audio on Fb for iOS and Android, in addition to on focused surfaces on Instagram, resembling Reels and Tales. We encourage you to put in the most recent model of Fb and Instagram apps on iOS 13+ and Android 9+ to make sure which you could expertise it.

Acknowledgements

This work is the collective results of all the Video Infrastructure and Instagram Media Platform groups at Meta in collaboration with Fraunhofer Institute for Built-in Circuits IIS. The writer wish to lengthen particular due to Abhishek Gera, Tim Harris, Arun Kotiedath, Edward Li, Meng Li, Srinivas Lingutla, Denise Noyes, Mohanish Penta, David Ronca, Haixia Shi, Mike Starr, Cosmin Stejerean, Jithin Parayil Thomas, Simha Venkataramaiah, Juehui Zhang, Runshen Zhu, and the engineering workforce at Fraunhofer Institute for Built-in Circuits IIS.