AI Music Transcription: Revolutionizing Music Analysis & Creation

By: Verbit Editorial
woman playing a keyboard

Although we usually think about music as an auditory medium, transcribing music to a readable format is a critical part of the production process for many songwriters, composers and instrumentalists. By transcribing a song, it becomes easier to share it with other musicians and to recreate it in future performances. However, manually transcribing music can be tedious and time-consuming. That’s why many musicians choose to take advantage of AI-powered music transcription tools.

These automatic music transcription solutions use advanced AI software to decode a piece of music and represent its various elements on a page. Let’s discuss some of the basics of AI music transcription and examine how this emerging technology can help musicians from all walks of life more easily share their compositions with the world.

Understanding AI Music Transcription

AI music transcription technology has evolved significantly over the last several years and has revolutionized the music transcription and notation process along the way. These software solutions use advanced learning models to take audio input and convert it to written sheet music. We don’t often think about the role of machine learning in music, but today’s musicians have a commanding arsenal of AI-powered tools at their disposal to help in their composition and production processes.

Automatic Music Transcription Techniques

Most AI music transcription tools basically perform audio to sheet music conversion. Essentially, these tools allow users to upload an audio recording that the AI then analyzes and convert into sheet music. To accomplish this task, the AI must undergo training to properly identify different musical notes and their durations with pitch detection algorithms and other types of music analysis technology. The software must also be capable of assigning the corresponding music notation symbols to these elements and arranging them into a properly formatted piece of music.

Some music transcription software solutions work a little bit differently. Rather than generating sheet music from an audio recording, these tools instead convert audio files to MIDI files. MIDI files function more like sets of digital protocols and essentially encode the various elements of an audio recording into a file format that users can easily edit and manipulate with MIDI-compatible devices.

Converting an audio recording to a MIDI file can help a writer or producer render their rough recordings into more streamlined tracks that are easier to work with and share with other musicians during the production process. Many AI transcription tools can also generate sheet music from MIDI files to improve accuracy, further streamlining the digital music notation process.

Benefits of AI Music Transcription

Automatic music transcription technology is one of the most valuable recent innovations in music technology. The manual music transcription process can be pain-staking and laborious, especially for musicians without advanced knowledge of music theory and notation. AI music transcription tools can make this process more efficient and accessible to musicians and writers of all backgrounds, abilities and means.

There’s no shortage of music industry technology already involved in the production process, but incorporating AI in music production can save professionals valuable time and resources. Using AI to produce sheet music can help to ensure everyone who works on a recording project has access to the most accurate and easy-to-follow version of a composition while saving producers and artists the cost of hiring a professional to transcribe their music by hand.

AI Music Transcription Challenges

While AI-powered music transcription solutions are impressive and versatile, they are not without their faults. In music, transcription accuracy is vitally important to ensure that musicians continue to perform the composition correctly, well into the future. Artificial intelligence can often deliver highly accurate transcripts of music, but there are a few variables that can negatively impact a machine’s transcription accuracy. These include:

  • Poor audio quality: AI algorithms for music may struggle to accurately transcribe a composition if the original audio recording is low-quality or hard to understand.
  • Non-standard notation: Even with advanced musical genre recognition capabilities artificial intelligence music applications may not be capable of properly transcribing non-Western compositions or microtonal music.
  • High levels of difficulty: Extremely intricate compositions may be too complicated for some musical data analysis tools. AI software will also encounter difficulty if an original audio recording contained incorrect or unclear rhythms, notes and dynamics.

Even if an audio recording is well-suited for AI transcription, it’s important to understand that artificial intelligence may never fully capture all of the nuance present in a piece of music. When it comes to emotional interpretation in music, AI cannot compete with human music transcribers who have a more innate understanding of musical tone and expression. Human transcribers can also better understand subtle stylistic changes in rhythm and dynamics and how these elements convey emotion.

Music Transcription Studies and Findings

In a recent study performed at Stanford University, researchers attempted to convert raw .wav files of piano performances to sheet music using artificial intelligence. Drawing on previous AI music transcription studies, Stanford’s research noted that commercial AI music transcription software still faces significant challenges with respect to transcription accuracy.

For this reason, Stanford’s process involved the use of a type of acoustic model known as a Convolutional Neural Network (CNN) to generate music scores. Stanford’s acoustic modeling process was capable of achieving an accuracy rate of over 98%, though researchers determined that additional machine learning would be necessary to make this tool effective with a broader music catalogue.

woman working on her laptop

Transcribing Music and Song Lyrics

AI music transcription technology shows great promise and has the potential to make the music composition and production processes more accessible and efficient for future generations. As these tools continue to learn and evolve, experts expect that AI solutions will one day be capable of generating sheet music and MIDI files with accuracy rates that rival those of human transcribers. By making the music transcription process more accessible and efficient, AI music transcription tools can support artists and producers of all education and skill levels and make the music production process more equitable for all.

For more information about AI transcription tools or to learn how you can easily transcribe your song lyrics, reach out to speak with the Verbit team. We offer a wide variety of AI-powered technology solutions to make audio and video content more accessible and engaging.