---
license: mit
library_name: pytorch
pipeline_tag: audio-classification
tags: [audio, music, chord-recognition, chord-detection, automatic-chord-recognition, music-information-retrieval, mir, hcqt, btc]
datasets: [guitarset]
metrics: [accuracy]
---

# BTC-HCQT — an HCQT variant of BTC for chord recognition

An HCQT (Harmonic-CQT) front-end variant of **BTC** (Park et al., ISMIR 2019) for **automatic chord recognition / chord detection** — turning audio into a time-stamped chord progression.

**Honest result:** on a reproducible mir_eval benchmark over held-out public data (GuitarSet, Schubert Winterreise), this model **ties baseline BTC** — it does **not** clearly beat it. Shared as a reproducible benchmark, an honest negative result, and an extensible HCQT base — not a new state of the art.

## Benchmark (held-out, public data, duration-weighted %)

| Model | GuitarSet root / 7ths | Schubert root / 7ths / mirex |
|---|---|---|
| baseline BTC | **80.9 / 64.6** | 73.1 / 55.3 / 64.1 |
| **this model (BTC+HCQT, Beatles-FT)** | 80.5 / 63.0 | **73.8 / 55.6 / 65.3** |

A dead heat — BTC noses ahead on guitar, this model noses ahead on classical, every gap within the 95% confidence intervals.

## Usage, code & full benchmark

Code, weights, the reproducible mir_eval harness, and a guide to extend the HCQT base to melody/bass/transcription: **https://github.com/marcusfkelley/btc-hcqt**

## Limitations & honest notes

It **ties** BTC; for accuracy alone, baseline BTC is the simpler choice. An early in-house metric suggested big 7th gains — that was a **recall artifact** (over-calling 7ths); on frame-wise mir_eval it disappears, so always evaluate with standard metrics and confidence intervals. For pure note transcription, purpose-built tools (basic-pitch, MT3, Omnizart) will outperform a from-here build — HCQT is a strong base to *extend* toward melody/bass/transcription, not a finished transcriber.

## Source

Built by [Selekt](https://selektaudio.com) — cleared-sample and music-analysis tools for producers and composers; chord recognition powers features like our chord-progression search. Honest writeup: https://selektaudio.com/chord-recognition

Built on BTC (Park et al., ISMIR 2019, MIT). HCQT: Bittner et al., ISMIR 2017.