Have you ever found yourself enchanted by a captivating song but clueless about its title or artist? Well, you’re not alone. Many of us have experienced that moment of musical curiosity, and that’s where Shazam comes to the rescue. In this article, we’ll explore how Shazam works, unveiling the secrets behind its remarkable ability to identify songs with astonishing accuracy.
But before we get into how the app works, let’s have a look at some startling facts about Shazam.
A brief history
Shazam was launched in 1999 by Chris Barton, Philip Inghelbrecht, Avery Wang, and Dhiraj Mukherjee. In 2018, Apple acquired Shazam for $400 million, making it one of the biggest acquisitions of any mobile app at the time. As of now, Shazam is not only available in Apple App Store, but also on Android, macOS, iOS, Wear OS, watchOS, and as a Google Chrome extension.
Stunning facts about Shazam
Shazam boasts an impressive global monthly user base of over 225 million as of September 2022, and its growth shows no signs of slowing down. To enhance its ability to recognize songs and TV/video content, Shazam has secured a remarkable 200 patents. Furthermore, the app is home to a staggering collection of over 12 billion tags, allowing users to categorize music and video content based on their preferences.
Delving into intriguing trivia, we discover that the most sought-after (Shazamed) song to date is “Dance Monkey,” with a record-breaking 41 million searches. Additionally, Drake stands tall as the most Shazamed artist of all time, accumulating an astounding 350 million hits.
What is Shazam?
Shazam is an incredibly popular music recognition app that acts as your personal music detective. Imagine being in a coffee shop or browsing through a store, hearing a mesmerizing song that catches your attention. Shazam is there to help you find that song effortlessly. All you need to do is open the app and record a few seconds of the song playing.
How Shazam Works
Shazam’s technology is built upon a proprietary system developed by Avery Lin-Chun Wang, the co-founder and chief data scientist of the app. This technology revolves around the creation and utilization of audio fingerprints, which form the core of Shazam’s remarkable recognition capabilities.
Audio Fingerprinting: The Secret Sauce
Shazam’s audio fingerprinting technology enables it to match unlabeled audio content to corresponding tracks in its vast music database. When you “Shazam” a song, the app quickly generates an audio fingerprint based on the recorded sound captured by your smartphone or PC microphone. This audio fingerprint is then uploaded to Shazam’s server for further analysis.
Decoding the Fingerprint: From Spectrograms to Matches
To better understand how Shazam works let’s delve into the concept of an audio fingerprint. An audio fingerprint is a condensed digital summary of audio signals, used to identify and locate similar items in a database. Shazam creates unique fingerprints for each song in its database by extracting crucial data points from spectrograms.
Spectrograms are three-dimensional graphs that represent sound, showcasing the changes in frequencies over time while considering volume or amplitude. By focusing on the defining notes and ignoring most of the song’s information, Shazam can swiftly search its vast database and provide accurate matches for song queries.
Identifying Songs in Noisy Environments
You might wonder how Shazam manages to identify songs even in noisy environments. To ensure accuracy, Shazam relies on song recordings that are relatively free from background noise and distortion. When you record a song in a noisy place using the app, Shazam focuses on the notes with the highest energy to create the audio fingerprint. As long as the background noise level isn’t high enough to distort the crucial data, Shazam can successfully find a match.
When Shazam Falls Short: Limitations of Song Identification
While Shazam is an impressive tool for identifying songs, it does have its limitations. There are certain situations where Shazam may struggle to recognize a song:
- Distorted Recording: High levels of background noise can distort the spectrogram data, resulting in a different audio fingerprint than the original song. In such cases, Shazam may not find a match and display a “Song not Known” dialogue.
- Live Music: Shazam faces challenges when identifying music from live performances. The audio recorded during live performances may differ from the original song used to create the audio fingerprints. Shazam can only identify a song during a live performance if the band faithfully recreates the original recording.
- Voice Recordings and Humming: Shazam’s algorithm is designed to identify prerecorded music and cannot recognize songs based on voice recordings or humming. For Shazam to identify a song you’re singing, you would need to replicate the exact vocals and instrumentals with the original tempo of the recording.
Exploring Alternatives to Shazam
Shazam is the pioneer and most widely used music identification app, however, there are other alternatives available. SoundHound, Musixmatch Lyrics, and Genius are popular alternatives that can identify songs playing around you. Musixmatch and Genius primarily help identify lyrics, while SoundHound competes closely with Shazam in song recognition.
Shazam has truly revolutionized the way we explore and discover music. Through its audio fingerprinting technology, Shazam enables us to uncover the mysteries behind our favorite songs with remarkable accuracy. Although it has its limitations in certain scenarios, Shazam remains an indispensable tool for music enthusiasts worldwide.
Next time you find yourself captivated by a melody, let Shazam work its magic and guide you on a musical adventure like no other.