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DialogueSidon-bf16
mlx-community/DialogueSidon-bf16
DialogueSidon-bf16 is a machine learning model from mlx-community. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for mlx-audio. The card lists the license as cc-by-nc-4.0.
Two-speaker dialogue separation and restoration, with 24 kHz mono stems. Converted from sarulab-speech/DialogueSidon for use with mlx-audio.
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At a glance
- Library
- mlx-audio
- License
- cc-by-nc-4.0
- Model type
- dialogue_sidon
- Access
- Public
- Created
- Sep 6, 2026
- Updated
- Sep 6, 2026
- SHA
- 5d42379f
Base models
Model card
From the Hugging Face model README
DialogueSidon
Two-speaker dialogue separation and restoration, with 24 kHz mono stems. Converted from sarulab-speech/DialogueSidon for use with mlx-audio.
from mlx_audio.sts import load
from mlx_audio.audio_io import write
model = load("mlx-community/DialogueSidon-bf16")
result = model.separate("dialogue.wav", num_steps=30, seed=0)
for i, speaker in enumerate(result.speakers, 1):
write(f"speaker_{i}.wav", speaker, result.sample_rate)
The two channels are anonymous speaker slots. Long recordings use overlapping
chunks and waveform correlation to maintain channel assignment. Consistency
across silence is not guaranteed. This is an offline generative model, so the
stems need not sum to the mixture. The default chunk and overlap are 20 and 5
seconds; use chunk_seconds=None for whole-file inference when memory permits.
The checkpoint retains CC-BY-NC-4.0. Original model by Wataru Nakata, Yuki Saito, Kazuki Yamauchi, Emiru Tsunoo, and Hiroshi Saruwatari (SaruLab). See the original model card and Sidon implementation.
- Library
- mlx-audio
- Type
- dialogue_sidon
- License
- cc-by-nc-4.0
- Created
- Sep 6, 2026
- Updated
- Sep 6, 2026