| --- |
| license: mit |
| library_name: pytorch |
| datasets: |
| - JacobLinCool/taiko-1000-parsed-clean |
| tags: |
| - audio-to-symbolic |
| - chart-generation |
| - from-scratch |
| - hierarchical-transformer |
| - music |
| - rhythm-game |
| - taiko |
| --- |
| |
| # SoftChart V1.8 Hierarchical Scratch |
|
|
| SoftChart V1.8 generates Taiko no Tatsujin-style charts directly from log-mel audio. This release is a compact hierarchical encoder-decoder trained **from scratch** on [`JacobLinCool/taiko-1000-parsed-clean`](https://huggingface.co/datasets/JacobLinCool/taiko-1000-parsed-clean); it does not use an external pretrained model or an external song planner. |
|
|
| The model combines a whole-song section encoder, a local rhythmic-skeleton auxiliary head, dual time/slot generation, and a beat/downbeat head. The public Space uses time-mode generation for arbitrary uploads, then uses the beat head only to estimate BPM and quantize the exported TJA. Exact slot generation is reserved for inputs with a complete, trusted rational meter grid including a terminal edge. |
|
|
| ## Architecture |
|
|
| | Item | Value | |
| |---|---:| |
| | Parameters | 8,985,091 | |
| | Audio encoder / chart decoder | 4 / 4 layers | |
| | Hidden size / attention heads | 256 / 8 | |
| | Feed-forward size | 960 | |
| | Hierarchical section encoder | 2 layers, FFN 512 | |
| | Vocabulary | 1,810 tokens | |
| | Audio input | 22,050 Hz, 128-bin log-mel | |
|
|
| Enabled capabilities are `hierarchical_ctx`, `aux`, `dual`, `beat_head`, and `clean_phase`. Legacy external plan conditioning is disabled. |
|
|
| ## Frozen evaluation |
|
|
| The locked test split contains 120 songs and 503 authored/time charts. Exact-slot results cover only the 127 charts whose parsed authored meter has a fully bounded-safe prefix. |
|
|
| | Metric | Locked test | |
| |---|---:| |
| | Exact-slot micro F1 (bounded-safe prefix) | 0.6810 | |
| | Full-song time F1 @ 25 ms | 0.4715 | |
| | Full-song time F1 @ 50 ms | 0.5972 | |
| | Mean per-chart median timing offset | 9.39 ms | |
| | Don/ka accuracy on 50 ms matches | 0.6551 | |
|
|
| These metrics compare against one authored chart even though chart design permits multiple valid answers. They do not establish human-rated groove, fun, or playability. The release has one training seed and no fair same-split V1.6/V1.7 retraining baseline. |
|
|
| Known limitations include weak note-type decisions relative to onset placement, under-generation of rolls/balloons, repetitive slot-mode motifs, and beat-grid ambiguity outside stable 4/4 material. |
|
|
| ## Use |
|
|
| The easiest supported interface is the [`JacobLinCool/softchart`](https://huggingface.co/spaces/JacobLinCool/softchart) Space. Programmatic loading uses the `softchart` package from the [source repository](https://github.com/JacobLinCool/SoftChart): |
|
|
| ```python |
| from softchart.generate import load_hf, generate_song |
| |
| model = load_hf("JacobLinCool/softchart-v18", device="cuda") |
| chart = generate_song( |
| model, |
| log_mel, |
| course="oni", |
| level=9, |
| device="cuda", |
| greedy=True, |
| ) |
| ``` |
|
|
| Audio preprocessing is part of the model contract in `preprocessor_config.json`: FFmpeg decodes stereo float32 at 22,050 Hz, channels are averaged arithmetically, and a periodic-Hann STFT (`n_fft=2048`, `hop_length=256`) is projected to 128 mel bins before natural-log compression. |
|
|
| ## Artifact provenance |
|
|
| - Source checkpoint SHA-256: `2a7a75f720369db03e5c114eff065de90ccc864259495463287509682c6352db` |
| - `model.safetensors` SHA-256: `68d924542033c1ad234ed23329e469cd5caaea4aa72dcfb83dec3a0d76f1295f` |
| - Preprocessing contract SHA-256: `2d8c542f628decc16b0fdd37befa9eff71b1734da29cf4556943260c2c8c2636` |
| - HF export round-trip verification: passed |
|
|
| Released under the MIT license. |
|
|
