WAV to MIDI Drums — Free AI Drum Transcription

What is WAV-to-MIDI drum transcription?

WAV-to-MIDI transcription converts an audio recording of drums into a Standard MIDI File. Each hit in the audio becomes a MIDI note, mapped to the appropriate General MIDI drum number — kick on note 36, snare on 38, closed hi-hat on 42, and so on. The result is a producer-editable MIDI clip: you can swap kits, rearrange hits, change velocities, and re-quantize without going back to the original audio.

Traditional approaches use peak-following plus simple frequency-band classifiers, which break on overlapping hits and busy beats. CedarGrooveNET uses a transformer-based model called DrumTranscriber v2 trained specifically on drum recordings — it tracks each drum element separately and produces clean, multi-instrument MIDI even for dense fills.

How CedarGrooveNET does it

Four steps from audio to editable MIDI:

1. Drop your audio file. Drag a WAV, AIFF, or MP3 into the app or browser. Mono or stereo, 22 kHz to 96 kHz sample rate.
2. Tempo and beat detection. CedarGrooveNET locks onto the BPM and finds the downbeat so the resulting MIDI aligns to a usable grid.
3. Multi-instrument transcription. A transformer model produces a separate event stream for each drum element (kick, snare, hi-hat, toms, crash, ride, clap) at frame resolution.
4. Grid mapping and export. Events are quantized onto the 16-step grid, rendered into the editable drum machine, and ready to export as a Standard MIDI File.

The whole pipeline runs locally — there is no upload step and no queueing. On a recent Mac, a 4-bar loop transcribes in under a second.

Supported formats and genres

Audio input: WAV (PCM 16-bit and 24-bit), AIFF, and MP3. Mono and stereo. Sample rates from 22.05 kHz to 96 kHz; everything is internally resampled to 44.1 kHz before inference.

MIDI output: Standard MIDI File (.mid), single drum track, GM percussion mapping (channel 10). Includes velocities derived from the original audio dynamics.

Genre presets for continuation: after transcription, you can extend the pattern using one of the built-in genre models — Drum & Bass, House, or Rock. Each is a separate encoder-decoder LSTM trained on style-specific corpora.

Why local-only matters

Most "AI" audio tools today require uploading your stems to a cloud service. That's a problem if you're working with unreleased material, signed material, or anything you'd rather not put on someone else's GPU. CedarGrooveNET runs the entire pipeline — transcription model, generation model, grid renderer — on your own machine, using either the Universal macOS app or the in-browser ONNX runtime.

Practical implications: no rate limits, no monthly subscription, no waiting in a queue, no audio ever leaving your device, and the tool works offline on a plane. The macOS app is universal binary (Apple Silicon native + Intel x86_64) and weighs in at 156 MB, including the bundled ONNX models.

Comparison vs alternatives