BandConvert – Transcribe multi-instruments audios into sheet music

Hacker News

BandConvert is an advanced online application that transcribes any polyphonic audio file (MP3, WAV) or YouTube video containing multiple instruments - such as those played by bands, orchestras, or ensembles - into professional-quality sheet music and MIDI/MusicXML files. Thanks to an AI engine specialized in multi-instrument recognition, BandConvert can detect and separate each instrument layer, identify pitch, tempo, rhythm, time signatures, clefs, and even subtle articulations. The result is an accurate, clean, and editable transcription available in several formats: PDF for printing, MIDI for editing, and MusicXML for importing into music production software. Entirely web-based and user-friendly, BandConvert offers musicians, music teachers, composers, and arrangers a powerful solution to convert complex recordings into full orchestral scores within seconds, no software installation required. Try BandConvert for free and simplify your musical transcription process: https://latouchemusicale.com/en/apps/bandconvert/

Visit product View on Hacker NewsJun 25, 2025

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3points

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Indie HackersFits the IH revenue-focused audience · Strong signals: para, ios · Missing: supports, reddit linkedin, podcasting

88%88% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

AppSumoStrong fit for a featured deal · Strong signals: friendly · Missing: plus, platform, intuitive

59%59% predicted probability of success on AppSumo, based on ML models trained on real launch data.

TrustMRRLess likely to generate early MRR · Strong signals: ios, apps, video · Missing: mobile apps, personal, entrepreneurs

47%47% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Hacker NewsMay not resonate with HN audience · Strong signals: ide, io · Missing: https docs, excited, just released

37%37% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

Product HuntUnlikely to reach the leaderboard · Strong signals: apps, user, recordings · Missing: mac, agents, macos

24%24% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Strong signals: arr · Missing: mrr, revenue, profit

11%11% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Strong signals: audio · Missing: web3, chat, crypto

1%1% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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