STT/ASR - onnx
Collection
OVOS STT/ASR models for onnx-asr (ONNX runtime). Most ship fp32 + int8 (set quantization: int8 for faster/smaller CPU inference). • 233 items • Updated • 2
How to use OpenVoiceOS/asr-uz-fastconformer-large-onnx with NeMo:
import nemo.collections.asr as nemo_asr
asr_model = nemo_asr.models.ASRModel.from_pretrained("OpenVoiceOS/asr-uz-fastconformer-large-onnx")
transcriptions = asr_model.transcribe(["file.wav"])ASR model exported to ONNX for the onnx-asr library and the ovos-stt-plugin-onnx-asr OpenVoiceOS STT plugin. Ships both the RNNT head (default) and the CTC head.
Language: Uzbek. Converted from uzinfocom-edu-ai/asr-uz-fastconformer-large, a FastConformer Hybrid Transducer+CTC model (EncDecHybridRNNTCTCBPEModel, ~120M parameters) fine-tuned on ~701 hours of curated Uzbek speech.
Reported WER (RNNT, source model card): 16.01%.
import onnx_asr
model = onnx_asr.load_model("OpenVoiceOS/asr-uz-fastconformer-large-onnx")
print(model.recognize("audio.wav"))
stt:
module: ovos-stt-plugin-onnx-asr
ovos-stt-plugin-onnx-asr:
model: OpenVoiceOS/asr-uz-fastconformer-large-onnx
lang: uz
Original model by uzinfocom-edu-ai, released under the Apache 2.0 license: uzinfocom-edu-ai/asr-uz-fastconformer-large.
Base model
nvidia/stt_uz_fastconformer_hybrid_large_pc