Nemotron Streaming 0.6B - WER Benchmark Results
Model: nvidia/nemotron-speech-streaming-en-0.6b
Dataset: LibriSpeech test-clean
Chunk size: 1.12s
Results
10 Files
| Mode |
WER |
Errors |
Words |
pad_and_drop_preencoded=False |
1.79% |
3 |
168 |
pad_and_drop_preencoded=True |
3.57% |
6 |
168 |
100 Files
| Mode |
WER |
Errors |
Words |
pad_and_drop_preencoded=False |
1.88% |
- |
- |
NVIDIA Claimed
| Dataset |
WER |
| LibriSpeech test-clean (1.12s chunks) |
2.31% |
Notes
pad_and_drop_preencoded=False: Better WER, but cannot be exported to ONNX/CoreMLpad_and_drop_preencoded=True: Worse WER (~3%), but required for ONNX/CoreML export- NVIDIA's 2.31% likely uses
pad_and_drop_preencoded=True on full 2620 files
- Our implementation uses
conformer_stream_step API with CacheAwareStreamingAudioBuffer
Run Benchmark
cd nemotron-speech-streaming-0.6b/coreml
uv sync
uv run python benchmark_wer.py --num-files 100
