How AI Lyric Transcription Works

Transcribing the lyrics of a recorded song is harder than transcribing speech. A sung vocal carries instruments, reverb, extended syllables, harmonies, and stylized pronunciation that ordinary speech-to-text engines were never trained to handle. TuneMason approaches lyric transcription as a music problem, not a speech problem.

The process starts with vocal isolation. TuneMason separates the lead vocal from the instrumental bed so the transcription model focuses on the voice and is not confused by drums, guitars, or synths. Once the vocal is isolated, the transcription model converts the sung audio into text.

When you already know the lyrics, reference-lyrics alignment takes over. Instead of guessing every word from sound alone, TuneMason matches your provided lyrics against the vocal performance. This reduces sound-alike errors, improves the handling of proper names and unusual words, and produces more reliable line-level timing.

Next comes timestamp alignment. TuneMason detects the vocal sections, shapes the recognized text into readable subtitle lines, and snaps each line onto the waveform with precise start and end times. Uncertain words and timings are flagged for review, so you only need to check the lines that matter.

Finally, TuneMason exports your subtitles in the format your workflow needs — SRT for YouTube, DaVinci Resolve, Premiere Pro, and CapCut, plus VTT and LRC for karaoke and web players. Editing lyrics, adjusting timestamps, and re-exporting never consume processing credits; only running a new AI job does.

The result is a timestamped lyric file you can drop straight into any video, karaoke, or subtitle workflow — without fixing every line by hand.