Songmastr
Automated Song Mastering with AI

Songmastr
Freemium
From 4$

Home: https://www.songmastr.com

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What is Songmastr?

Songmastr is an online service that leverages artificial intelligence to master songs. The technology is based on the open-source library Matchering. It allows users to upload a song and a reference track, and the AI will adjust the RMS, FR, peak amplitude, and stereo width of the user's song to match the reference.

This service supports both WAV and MP3 files, with a maximum file size of 80MB and a song length limit of 10 minutes. Files are deleted within 24 hours of processing. Songmastr requires no software installation or user registration.

Features

  • Automated Mastering: Masters your track using AI based on a reference track.
  • Reference Track Matching: Adjusts RMS, FR, peak amplitude, and stereo width to match the reference.
  • WAV/MP3 Support: Accepts both WAV and MP3 files for input.
  • File Size/Length Limits: Processes songs up to 10 minutes and 80MB.
  • Data Privacy: Deletes uploaded files within 24 hours.
  • No Registration: Use the service without any software or registration.

Use Cases

  • Mastering a song to match the sound of a professionally produced track.
  • Quickly improving the overall sound quality of a mixed song.
  • Achieving consistent loudness and sonic characteristics across multiple tracks.
  • Preparing a song for distribution on streaming platforms.

FAQs

  • How to pre-process the target track?
    Your song must be properly mixed before uploading. Leave some volume headroom on your mixed track (typically -6db). You can apply some compression, but do not apply a limiter, as limiting will be done during mastering.
  • How to choose the reference track?
    The reference track must have be in the same genre and "vibe" as your song. If you are mastering a beat or instrumental track, preferably choose a reference without a singer. If you upload your own reference track, make sure it is good quality and at a normal commercial volume.

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Songmastr Uptime Monitor

Average Uptime

100%

Average Response Time

844.07 ms

Last 30 Days

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