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 supply enhanced audio for options like Reels and Tales. 

At Meta, we serve each media use case possible for billions of individuals the world over — from short-form, user-generated content material, similar to Reels, to premium video on demand (VOD) and dwell broadcasts. Given this, we’d like a next-generation audio codec that helps a spread of working factors with wonderful compression effectivity and trendy, system-level audio options. 

To handle these wants now and into the long run, Meta has embraced xHE-AAC because the car for delivering high-quality audio at scale.

The advantages of xHE-AAC

xHE-AAC is the newest member of the MPEG AAC audio codec household. The Fraunhofer Institute for Integrated Circuits IIS performed a considerable position within the improvement of xHE-AAC and the MPEG-D DRC commonplace.

As we speak, xHE-AAC is already offering a superior audio expertise on Fb and Instagram — together with on Reels and Tales — and has plenty of priceless options.

Loudness administration

With tons of of hundreds of thousands of uploads per day throughout Fb and Instagram, we obtain audio tracks with loudness ranges starting from silence to full scale, and the whole lot in between. 

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

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

As an alternative 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 by way of loudness metadata, for the optimum audio expertise based mostly on context. 

On account 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 fee audio

Most individuals who use our apps devour media on cell gadgets and count on 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 consumer expertise. 

To optimize high quality below dynamic bandwidth constraints, we produce a number of video and audio qualities to match various community circumstances at playback time. Regardless that we produce a number of audio lanes, we now have traditionally solely employed adaptive bit fee (ABR) algorithms to change video qualities throughout playback as a result of it’s tough to allow adaptive bit fee audio with out compromising high quality throughout lane transitions.

So as to allow seamless audio ABR, xHE-AAC introduces the idea of instant playout frames (IPFs) that comprise all the info mandatory to begin taking part in a brand new audio lane with out counting on knowledge from different frames. By inserting an IPF originally of every Dynamic Adaptive Streaming over HTTP (DASH) section and aligning the section durations of every lane, we will seamlessly swap between audio lanes throughout playback to supply the highest-quality audio at any accessible bandwidth whereas avoiding playback stalls.

After launching audio ABR on Fb for Android, we had been in a position to enhance consumer expertise by decreasing the variety of periods the place playback stalls. 

How we deployed xHE-AAC

We generate xHE-AAC bitstreams utilizing an encoder SDK offered by the Fraunhofer Institute for Built-in Circuits IIS, after which put together the ensuing audio information 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 go and carry out the precise audio knowledge compression on the second go. As an additional advantage, 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 similar to pattern fee and channel configuration are stored 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 atmosphere by configuring a goal loudness degree and DRC impact kind based mostly on context, and because of the embedded loudness metadata, we will adapt a single xHE-AAC bitstream to a wide range of audio consumption use circumstances, from headphones to system audio system and varied 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 at the moment?

You possibly can expertise xHE-AAC audio on Fb for iOS and Android, in addition to on focused surfaces on Instagram, similar to Reels and Tales. We encourage you to put in the newest model of Fb and Instagram apps on iOS 13+ and Android 9+ to make sure that you would be able to expertise it.

Acknowledgements

This work is the collective results of your entire Video Infrastructure and Instagram Media Platform groups at Meta in collaboration with Fraunhofer Institute for Built-in Circuits IIS. The writer want to lengthen particular because of 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 crew at Fraunhofer Institute for Built-in Circuits IIS.