Shazam: The Sound of the Ecosystem

Welcome to a new episode of the A-Positive Podcast where I observe the Apple culture and my daily use of Apple hardware, software, and services. In today's episode, I am going to dive into Shazam, the music recognition app that transformed from a small startup into a key component of Apple’s ecosystem. I will explore how Shazam, since its acquisition, has been integrated into the Apple experience.

Apple has integrated Shazam’s technology in several meaningful ways across its ecosystem, turning what used to be a standalone app into a core feature that enhances the Apple experience. For one, it’s built into Siri and there is no separate app required to use it. You can ask Siri “What song is this” or “Shazam this” to identify a song even if the app is not installed.

Secondly, there’s a deep integration with Apple Music as once a song is identified users can instantly play it in Apple Music or add it to a playlist with all the recognized songs synced across your personal devices. This feature is actually updated just last month as Shazam will now include songs from Control Center, Siri and other shortcuts, to this playlist.

Talking about Control Center, thirdly, there’s a dedicated shortcut making this a stealthy mode to silently listen and identify music super fast as you don’t have to open up your phone to access this. And now with the Action Button on iPhone 15 or 16 and the modifiable shortcut buttons on the lock screen you can access it even faster.

So, let’s dive in. Shazam’s core tech is audio fingerprinting, which is a technology that creates a unique digital summary, or, a fingerprint of an audio recording. This can be a song, a podcast, or any sound effect. It can quickly and accurately be identified from a large database, even if just a short clip.

Audio fingerprinting basically answers the question “What is this sound?”

It listens to a few seconds of audio, transforms it into data points, and matches it against a library of known audio fingerprints.

There are other real life examples of this technology like YouTube Content ID to flag copyrighted audio in videos or TV Apps to let you discover music from a soundtrack or even Accessibility tools to identify alarms or when a baby is crying.

Now, after the acquisition Apple kept the Shazam app available in the App Store, but made it ad-free, which improves the user experience and it integrates with other Apple features, like Handoff, App Clips, and Spotlight Search. Apple also made a point of aligning Shazam with its privacy principles, so that data isn’t used to build user profiles or sold to advertisers.

This technology benefits from Apple’s investment in on-device machine learning, making the identification process faster and more private, since audio doesn’t always need to leave the device. Even if you are using AirPods or playing audio through the phone itself, Shazam can detect songs running in the background or on nearby devices. This is because of the tight integration with iOS Audio API’s.

And, Apple didn’t just keep Shazam’s capabilities for its own apps. It also packaged the technology into an API called ShazamKit for third-party developers. It was announced at WWDC 2021 and it allows developers to use Shazam’s audio fingerprinting in their own apps. This means an app can analyze audio and either match it against the Shazam music catalog to identify songs, just like the Shazam app does. Or against a custom audio catalog that the developer provides. Notably, matching against custom catalogs is done offline and on-device.

This means that ShazamKit opens up many possibilities beyond music identification. For example, a developer can create a learning app that listens for a specific spoken phrase or sound cue in a video to trigger interactive content. There’s a demo that showed a developer using ShazamKit to count spoken words, illustrating that the framework can handle more than just songs. Essentially, any audio that can be fingerprinted, whether it’s speech, animal sounds or sound effects, it can be recognized if a reference library is provided.

The ShazamKit API also lets apps tie into the official Shazam song database (with user permission of course). This means a trivia game for instance, could confirm if the song playing in the room is the correct answer. Or a fitness app could detect what music is playing and tailor the workout intensity to its tempo.

Apple’s integration of Shazam’s core tech in the developer toolkit underscores the value of that acquisition as you get a decade-tested audio recognition algorithm, into the hands of any iOS developer. Apple has effectively turned Shazam into a feature of the operating system and a resource for innovation in the app ecosystem.

In a WWDC 2022 developer video an update to ShazamKit is demonstrated by video content matching to specific in-app tasks. It’s really cool and I will provide the link to the video session for you to check out. https://developer.apple.com/videos/play/wwdc2022/10028/

One of the most powerful but yet often overlooked feature of Shazam technology is DJ mixes. This is actually one of my personal favorites as before I would search for podcasts that hosted DJ mixes. I actually had a podcast like this myself, this was back in 2007 can you believe it? Back then when I told people I had a podcast they would say that I’m weird or asked me what a podcast was. I also used apps like SoundCloud or Mixcloud or even YouTube for DJ mixes.

Before Apple’s acquisition of Shazam, long-form DJ sets were notoriously difficult to monetize on streaming platforms. The issue was tracking which songs were used, for how long, and ensuring that the original artists and rights holders were paid fairly.

Shazam’s advanced audio fingerprinting changed that.

The recognition engine can scan the entire DJ set, identifying each song embedded within the set — even if it’s just a short snippet, layered under effects or transitions. These identifications allow Apple to automatically assign royalties to the correct artists, labels, and publishers without requiring a detailed tracklist or manual reporting.

This has been a game-changer for the music industry.

In 2021, Apple announced that official DJ mixes would be added to Apple Music — fully licensed, artist-friendly, and royalty-enabled. Thanks to Shazam, artists now get paid even when their tracks appear inside a remix, mashup, or live performance.

This innovation not only protects the artist of a particular song in the live performance, but also supports the DJ culture within the streaming world. Platforms like Cercle, Boiler Room and Defected Records have since partnered with Apple Music, bringing high-quality DJ content to mainstream audiences.

From the listener’s perspective, the benefits are immediate. Apple Music now displays the names of individual tracks within a DJ mix, if it can be recognized by Shazam of course. It allows users to skip or scrub to specific songs inside the mix. So if you’re listening to a festival set or a club mix on Apple Music and love the third track, you can see what it is and jump right to it. From a technical standpoint, this is Shazam’s fingerprinting at an impressive scale.

In essence, Shazam has become the silent engine behind one of Apple Music’s most progressive features: turning an untrackable art form into a transparent, fair, and rewarding experience for all contributors.

As Apple steps into Augmented Reality with devices like the Vision Pro, Shazam’s technology is also finding new contexts. Enabling users to identify a song playing in their environment or within an app using just their voice or a glance. This can enrich mixed-reality experiences. For instance, imagine wearing Vision Pro and having the system display the title of a background song as it plays around you. In fact, third-party developers are already exploring this. There’s one Vision Pro app, called NowPlaying, that lets users search music information in a spatial interface and uses ShazamKit to identify songs in the environment. This could be something on a TV show or something that is playing on an old record player. This demonstrates how Shazam’s capabilities can enhance augmented reality experiences by bridging the gap between the physical audio around us and digital information.

Now, beyond Vision Pro, Apple TV also benefits from Shazam via Siri. With tvOS, users can ask the Siri Remote what song is playing during a show or movie. This is the same technology that iPhone uses, now helping people quickly find music from their favorite TV scenes. But also in services like Apple TV+ we now have insights showing the music that is playing at that particular time in the movie or TV show for you to easily add it to your Apple Music library with the tap of a button. Now I'm not sure if this is part of ShazamKit, but I wouldn't be surprised.

While Shazam specializes in music, Apple has expanded the idea of audio awareness to other domains, including accessibility and safety. Recent iOS versions introduced a Sound Recognition feature that can listen for specific ambient sounds like doorbells, a baby crying or a fire alarm and alert the user. This is designed to help people with hearing impairments or anyone who wants an iPhone to monitor important sounds. Sound Recognition on iPhone uses on-device machine learning to classify sounds, and although it doesn’t use Shazam’s music database, Apple’s overall expertise in audio processing undoubtedly helped bring this feature to life.

Similarly, Apple’s HomePod speakers gained the ability to detect alarm sounds in 2023. The HomePod can continuously listen for the sound signature of a smoke alarm or carbon monoxide alarm and send a notification to your iPhone if one is detected . Apple calls this Sound Recognition as well, and it extends the awareness of a smart home by leveraging always-on device microphones for safety.

These accessibility and safety-oriented features show Apple applying “audio fingerprinting” in a broader sense – not to identify a song by name, but to recognize patterns like a siren or a door knock. And they run locally to preserve privacy. We haven’t seen Apple explicitly say Shazam’s team worked on these, but it’s clear Apple’s emphasis on audio intelligence across devices grew after the Shazam acquisition. We now have devices that not only know what you’re listening to, but also can be aware of other sounds in your environment.

For example, my iPhone can alert me if my doorbell rings while wearing my AirPods, and my HomePod can quote unquote “Shazam” my smoke detector for my peace of mind. Together, these features underscore an ecosystem where audio signals are recognized and acted upon intelligently.

Apple’s purchase of Shazam has proven to be far more than just acquiring a music app. It was about absorbing a powerful audio recognition engine and the expertise behind it, to then embedding that across Apple’s ecosystem. Today, Shazam’s technology enhances user experiences in countless ways: we can instantly identify and save songs with Siri or a tap, discover new artists via Shazam-based charts in Apple Music or enjoy DJ mixes with full track transparency while ensuring all creators get paid, and even have third-party apps and devices that “understand” the soundscapes around us.

By integrating Shazam, Apple has made its devices more aware of music and sound, bridging the gap between the auditory world and digital services. This not only benefits us customers, but also benefits artists and creators, and opens new possibilities for app developers.

In a very real sense, Shazam’s DNA is now a part of Apple’s own rhythm – from your pocket to the HomePod to the concert in your Vision Pro, the world is full of recognizable sound. Apple has tuned in, and the result is an ecosystem that’s richer, more interactive, and more responsive to the sounds that define our lives.

This is very much how Apple decides to do an acquisition anyway. So if you hear someone say Apple should buy this or that company, think about it, how would Apple use the talent or technology from said company to enhance the ecosystem. Or better yet, ask that to the person convinced they should acquire said company. Anyway, that’s for another episode.