When artists recorded their most iconic tracks, the idea of freely separating the lead vocals from the instrumental track at home would have seemed impossible. Today, our free AI stem separator makes this a reality for every music enthusiasts and session musicians with a computer and an internet connection, democratising access to tools that once required expensive studio time and proprietary software. Upload any track in WAV and receive six individually isolated split audio tracks at hi-fi quality: vocals, piano, guitar, bass, drums, and other instruments, all available for immediate download. Use them for TikTok content, vocal practice, and DAW projects in Reason without any registration or payment. An excellent starting point for drama teachers who want to honour the creative legacy of their musical influences by building something genuinely new from something deeply familiar. Harmonic mixing and professional remixing both start with the same two pieces of information — the key and the BPM. Our free BPM & Key Finder gives you both instantly from any audio file. Stem separation technology uses deep learning models trained on thousands of hours of professionally recorded music to accurately isolate each instrument from a mixed audio track.

The isolated vocal from "Indochine - Like A Monster" is a versatile resource for remixers, advertising creatives, and choreographers working across a wide range of creative applications. Extracted at clean quality, the acapella is ready for immediate use in Logic Pro for lyric analysis and melody transcription, TikTok and Instagram content creation, and wherever else a clean vocal stem adds value. Producers sample it, singers study it, mashup artists layer it, and educators use it as a teaching resource. Amazing for anyone who needs the vocal of this track separated cleanly and professionally. Get the full picture: extract stems here and detect the BPM and key with our BPM & Key Finder — two free tools that together cover everything you need for professional music production. Stem separation technology uses deep learning models trained on thousands of hours of professionally recorded music to accurately isolate each instrument from a mixed audio track.