What Are Audio Stems? A Guide for Musicians and Producers

“Stems” is a term you’ll hear in music production, but it’s often used loosely. Here’s a clear breakdown of what stems actually are and why they’re useful.

The Basic Definition

In music production, stems are individual audio elements of a completed mix, grouped into separate files. Rather than a single stereo mix of the whole song, you get multiple files—one for the vocals, one for the drums, one for the bass, and so on.

The word “stem” in this context comes from audio production workflow. When delivering a mix for a film, TV show, or remix, engineers would provide multiple sub-mixes (stems) so the receiving party could adjust the balance of elements without having to re-mix everything from individual tracks.

Stems vs. Tracks vs. Multitracks

These terms get confused, so it’s worth distinguishing them:

• Multitrack — The individual recorded elements (one track per instrument, microphone, or synthesizer). A multitrack session might have 50+ individual audio files.
• Stems — A subset of those tracks combined into logical groups. A typical stem set might include: vocals, drums, bass, and “everything else” (pads, guitars, synths).
• Mix — The final stereo combination of everything.

Stems sit between multitracks and the final mix in terms of granularity.

The Most Common Split: Vocal + Instrumental

For many practical purposes—karaoke, practice, remixing—you only need two stems: the vocal and the instrumental (everything else). This is the most commonly requested and most achievable split.

More complex stem sets (separating drums, bass, melody, and “other”) are also possible but harder to execute cleanly, because the boundaries between elements are less distinct than the vocal-versus-everything-else split.

Why Are Stems Useful?

For remixers: Original stems allow you to rebuild the arrangement around the original elements. You can keep the vocal, replace the beat, and add your own production underneath.

For live performers: Many live acts use stem playback instead of full backing tracks. This lets the engineer adjust the mix to suit the venue without the performer needing to carry a laptop running a DAW.

For music licensing: When licensing music for film or advertising, clients often request stems so they can adjust the balance for sync—fading music under dialogue, emphasizing certain elements, or cutting to different sections.

For producers and educators: Studying how a mix is constructed is easier when you can isolate elements. Listening to just the drums from a famous record reveals arrangement and production decisions that are inaudible in the full mix.

For practice: Removing vocals lets you practice singing; removing instruments lets you practice playing. This is covered in more depth in our guide to practicing singing at home.

Getting Stems from a Song

There are three ways to get stems:

1. Directly from the artist or label. Original stems are occasionally released for remix competitions or licensing. They’re always the highest quality option.

2. Purchasing stem packs. Some artists sell stem sets directly or through platforms like Splice.

3. AI audio separation. Tools like SongSplit AI use machine learning to estimate stems from a mixed recording. This works on any song you have a DRM-free audio file of, without needing access to the original session.

AI separation is not equivalent to having the original stems—it’s an estimation. But for the vocal/instrumental split, modern AI tools produce results that work well for karaoke, practice, sampling, and many remix applications.

What AI Separation Can and Can’t Do

AI separation excels at the vocal/instrumental split because human voices have distinctive characteristics (formant structure, pitch range, typical reverb treatment) that differ from most instruments.

Separating individual instruments from each other—drums from bass from guitar—is harder, because these elements share frequency ranges, overlap in time, and interact in ways that make them harder to disentangle. Results vary considerably depending on the recording.

SongSplit AI focuses on the vocal/instrumental split, which is the most consistently useful and highest-quality application of on-device AI separation.

A Practical Starting Point

If you’ve never worked with stems before, the best way to understand them is to create some. Drop a song you know well into SongSplit AI, process it, and listen to each stem independently. Hearing familiar music broken apart reveals things about the arrangement and production that you don’t notice in the full mix.