metadata
language: be
tags:
- conformer
- transducer
- rnnt
- mlx
- apple-silicon
- speech-recognition
- asr
- belarusian
- nemo
license: cc-by-4.0
datasets:
- mozilla-foundation/common_voice_10_0
metrics:
- wer
base_model: nvidia/stt_be_conformer_transducer_large
pipeline_tag: automatic-speech-recognition
Conformer-Transducer (RNN-T) Belarusian (MLX)
Code: molind/mlx-conformer
NVIDIA's Conformer-Transducer Large model for Belarusian speech recognition, packaged for MLX inference on Apple Silicon.
Original model: nvidia/stt_be_conformer_transducer_large
Results
| Dataset | WER | Speed |
|---|---|---|
| CommonVoice 24.0 test (500 samples) | 6.29% | 7.6 samples/s |
Best open-source Belarusian ASR result we are aware of on CommonVoice 24.0.
Usage
pip install mlx numpy pyyaml sentencepiece torch
git clone https://github.com/molind/mlx-conformer
cd mlx-conformer
python mlx_conformer.py \
--download nvidia/stt_be_conformer_transducer_large \
--output models
python mlx_conformer.py \
--model models/stt_be_conformer_transducer_large \
--type transducer \
--audio test.mp3
Architecture
- 17 Conformer encoder layers, d_model=512, 8 heads
- LSTM prediction network (1 layer, 640 hidden)
- Joint network (640 hidden, ReLU)
- 1024 BPE vocabulary + blank
- ~120M parameters
License
Original model by NVIDIA, licensed under CC-BY-4.0.