Supertonic 3: F1200 single-thread, eight-step student
Selected model: models/round5-original50-student/. The user selected F1200 after comparing it with E400 and hearing no large difference on the supplied Korean development listening samples. This is limited listening feedback, not a MOS score or a perceptual similarity percentage.
F1200 uses unchanged FP32 duration/text/vocoder components and reduced-range dynamic INT8 for the vector estimator. Inference uses one CPU thread and eight actual denoising iterations. Its only teacher targets were the pinned original FP32 Supertone Supertonic 3, CFG4, 50 steps. The original 50-step trajectory is interpolated onto the student's eight-step time grid; the final target is the exact original final latent. The student is a learned approximation, not mathematically identical to CFG4 or the original model.
The F1200 vector SHA256 is 7c81ab7f0ddcc4266743701599a8708d2edd1be04285770f996e84a8bb5f4447. Source revision: 13fb103. Source and experiment records: GitHub project.
Optional2x package: F1200 with internal latent retiming
models/round8-latent-retime-g135/ preserves all F1200 learned weights. It runs eight actual denoising calls at internal1.35 duration and resizes24-channel fine latent frames inside the original vocoder to produce2x speech. No waveform tempo/pitch filter or extra learned head is used. Other requested speeds retain the native duration path. Default F1200 remains available unchanged.
Use the project runtime, which supplies the new target_frames vocoder input. The GitHub downloader pins this package's immutable revision and verifies file hashes.
python download_artifacts.py --purpose inference --model round8-latent-retime-g135
python synthesize.py 'μλ
νμΈμ. μ€λλ μ»΄ν¨ν°μμλ λΉ λ₯΄κ² μμ±μ μμ±ν©λλ€.' \
--model .hf-assets/model/models/round8-latent-retime-g135 \
--lang ko --voice M1 --steps 8 --speed 2 --output samples/fast.wav
The user confirmed less mechanical noise and acceptable pronunciation on a short male Korean A/B sample. This is limited listening feedback. On sixteen consumed validation contexts, KO CER is51/193(26.42%) and EN WER1/96(1.04%), versus native2x F1200's133/193 and68/96. Normal1.05 F1200 is5/193 and0/96. Substantial Korean errors remain. This is not an omission-free general model, independent test, MOS, or speaker-equivalence result.
Optional enginev4 on the shared EPYC7551 one-logical-CPU/1GB server has paired median speedups1.042x KO and1.047x EN over enginev2 with unchanged waveforms. Short2x RTF is about1.35, long2x1.32..1.33, normal1x about1.00, excluding loading/file I/O. There is no realtime guarantee or new ARM result. The package is standard ONNX; the optional Linux AVX2 kernel must be built separately from GitHub source and is not shipped here.
This graph transform needs no new training dataset or checkpoint. Existing original50 reproduction data and F1200 reproduction checkpoints remain unchanged. All package file hashes are added to asset_manifest.json; the upstream license is preserved. The engine and preparation source are recorded at GitHub commit 7704219; see its9th-round record for validation and failed trials.
Models retained
models/round5-original50-student/: selected F1200, 1,200 training updates; vector file48,903,928bytes.models/round5-original50-preview/: frozen E400 for listening comparison; not the default. Same architecture as F1200.models/cfg-mixed-v1-selected/: historical B baseline, retained for comparisons.models/cfg1024-v1-final/,models/mixed-v1-selected/: historical published experiments. Their quality/performance records do not apply to F1200.
Rejected derived-teacher training artifacts and the C/D model rejected for smearing/mechanical sound are not part of this release. No model pruning or retraining is planned after this F1200 selection; subsequent work optimizes the fixed-model engine.
Measured scope
On the shared EPYC7551 one-core, approximately1GB host, three alternating E/F process pairs gave F1200 medians5.594s/RTF1.0515 Korean and5.280s/RTF1.0702 English for the fixed short sentences. Loading and file writes are excluded; CPU affinity and ORT/BLAS threads are fixed to one. The sampled50ms memory monitor is not a cgroup limit. These measurements do not predict ARM speed. The historical ARM PR measures B, not F1200.
A four-sentence development pilot (KO2/EN2) had0/44 Korean character errors and0/20 English word errors for original50, B, E400 and F1200. It is too small for broad quality claims, and no fresh independent F1200 test has been evaluated. Existing test sets have already been consumed.
Minimal reproduction assets
reproduction/round5/original50-initial.pt and original50-step-01200.pt preserve the exact F1200 initialization and final checkpoint. The directory also contains training and initialization reports, corpus and a teacher-data audit. Intermediate checkpoints200β1000 and rejected workflows are excluded. E400 is supplied as an inference comparison package; its separate training checkpoint is omitted to limit size.
The companion dataset contains640train/128validation pairs from80/16 unique authored sentences, generated only by the original50-step teacher. No test trajectories were collected. The initialization reuses existing student weights as an initial value, never as teacher targets. Six replacement FFNs were previously fit only to original FP32 teacher activations. The uploaded initial checkpoint means those fits do not need to be repeated to reproduce this training stage.
See the source reproduction instructions. New training is not guaranteed bit-identical across hardware/library versions. asset_manifest.json lists SHA256/byte length for every artifact. Public downloads require no token. Source code has a separate license; all derivative model weights retain the upstream Open RAIL-M terms.