VibeVoice-ASR-BitNet

microsoft/VibeVoice-ASR-BitNet

作者
microsoft
任务
语音识别
下载量
91,479
点赞数
214
趋势分
4
许可证
mit
收录时间
2026/11/7

language:

  • en
  • zh
  • fr
  • it
  • ko
  • pt
  • vi license: mit pipeline_tag: automatic-speech-recognition tags:
  • ASR
  • quantization
  • cpu-inference
  • gguf
  • bitnet
  • multilingual library_name: ggml

VibeVoice-ASR-BitNet

GitHub Technical Report License: MIT

VibeVoice-ASR-BitNet is a compressed variant of VibeVoice-ASR optimized for real-time inference on edge CPUs — no GPU required. Through heterogeneous quantization, the model is compressed from 4.62 GB to 1.58 GB while achieving 1.6–2.3× faster inference than Whisper.cpp with real-time capability (RTF < 1) on as few as 3 CPU threads.

➡️ Code: microsoft/VibeASR.cpp ➡️ Report: VibeVoice-ASR-BitNet Technical Report ➡️ Base Model: microsoft/VibeVoice-ASR


🔥 Key Features

  • ⚡ Real-time on CPU — RTF < 1 with 3+ threads on commodity x86 (AVX2) and ARM (NEON) hardware
  • 📦 Compact — 1.58 GB total (2.9× compression from FP16), fits in edge device memory
  • 🌍 Multilingual — English, Chinese, French, Italian, Korean, Portuguese, Vietnamese, and more
  • 🔧 Custom SIMD Kernels — Fused operators within the ggml framework for both ARM and x86 platforms

Quantization Strategy

ComponentFP16QuantizedMethodCompression
VAE Tokenizer1.31 GB0.65 GBI8_S2.0×
LM Decoder3.32 GB0.92 GBI2_S + Q6_K3.6×
Total4.62 GB1.58 GB—2.9×

Evaluation

Inference Speed

Threads123468
RTF1.981.080.770.630.490.42
vs. Whisper.cpp2.28×2.12×1.86×1.86×1.71×1.55×

Benchmarked on AMD EPYC 7V13 (AVX2+FMA) with 20s audio. Bold = RTF < 1 (real-time).

Accuracy (WER%)

BenchmarkVibeVoice-ASR-7BVibeVoice-ASR-BitNetParakeetWhisperSenseVoiceFunASR
MLC-EN7.828.258.4013.5712.3911.36
MLC-FR16.0317.41————
MLC-IT15.6717.23————
MLC-KO9.8311.15————
MLC-PT22.4124.87————
MLC-VI20.1522.38————
AISHELL419.8327.45——22.5220.41
AMI-ihm17.4221.3621.9227.0730.8132.07
AMI-sdm24.1825.8726.3336.9248.1140.17
AliMeeting36.2140.58——38.7539.27
Fleurs-en4.735.214.093.996.844.93
Fleurs-zh7.928.35——5.567.00
Libri-clean2.172.411.491.982.781.58
Libri-other5.846.273.133.606.814.01
VoxPopuli4.925.185.267.198.636.46

Model Files

FileSizeDescription
vibeasr-vae-encoder-i8_s.gguf0.65 GBVAE tokenizer, I8_S quantized (ready to use)
vibeasr-lm-i2_s-embed-q6_k.gguf0.92 GBLM decoder, I2_S quantized (ready to use)
model-*.safetensors10.7 GBOriginal SafeTensors (for conversion)

License

This project is licensed under the MIT License.

Contact

This project was conducted by members of Microsoft Research. If you have suggestions, questions, or observe unexpected behavior, please contact us at VibeVoice@microsoft.com.

内容来源:Hugging Face 模型卡

在 Hugging Face 查看