Organization
MaAI
maai-kyoto
Models in Library11
Datasets in Library0
Models on Hugging Face36
Followers11
Compare the published evidence
This profile connects the 11 model and dataset records shown below to their upstream cards and sources. The library counts describe SAVRN's coverage, rather than this publisher's entire output.
Published tasks: Feature extraction.
Reported licenses: cc-by-4.0, cc-by-nc-nd-4.0, mit. Open a record to review its specific license and conditions.
Compare model specifications, source dates, and hardware estimates on the individual records. Publisher identity verification is separate from a model's quality, deployment readiness, or suitability for your work.
Models
This is a modified ONNX export of the Mimi audio codec encoder. It bypasses the Residual Vector Quantization (RVQ) to directly output continuous feature representations instead of discrete tokens. This preserves fine-grained acoustic details, making it ideal for downstream tasks like real-time dialogue analysis or speech emotion recognition. This model is a derivative work based on the "Mimi" model. Numbers below are illustrative (desktop CPU, FP32 ONNX vs PyTorch kyutai/mimi, streaming chunk emit=1280 @ 16 kHz, inference.py --compare). Your machine, thread counts, and ORT / PyTorch builds will shift them. Speed — RTF (processing time ÷ real-time audio length per chunk) In repeated 1-second…