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| Architecture | FastConformer-Transducer (RNN-T), cache-aware streaming |
| NeMo class | EncDecRNNTBPEModel |
| Tokenizer | single 2048-token Thai BPE |
| Latency knob | chunk_size × 80 ms → 1040 / 480 / 80 ms |
Multi-latency att_context_size | [[70,13],[70,6],[70,1],[70,0]] |
| Streaming CER (TVSpeech) | 19.4% @1040 ms · 16.4% @3200 ms |
| RTF (batch-1, H100 @1040 ms) | 0.020 (~50× real time) |
| Paired n-gram | typhoon-ai/typhoon-asr-streaming-115m-ngram |
typhoon-ai/typhoon-asr-streaming-nemotron-0.6b.1import nemo.collections.asr as nemo_asr
2
3model = nemo_asr.models.ASRModel.restore_from("typhoon-asr-streaming-115m.nemo",
4 map_location="cuda")
5model.eval()
6
7# offline (whole file)
8text = model.transcribe(audio=["clip.wav"])[0].text
9
10# true streaming: model.encoder.setup_streaming_params(chunk_size=13, left_chunks=2,
11# shift_size=13) + conformer_stream_step(...) — see demo/asr_engine.py in the repo.docs/SHALLOW_FUSION.md.att_context_size) and a
1-epoch Thai fine-tune on the Typhoon ASR Real-time corpus.