Sado is the name AlgorithVoice gives to STT Uz FastConformer Hybrid
Transducer-CTC Large P&C by NVIDIA Corporation, licensed under CC-BY-4.0
(https://creativecommons.org/licenses/by/4.0/). NVIDIA does not endorse
AlgorithVoice or this repository.

This repository is a copy of nvidia/stt_uz_fastconformer_hybrid_large_pc with
these files added, for use with sherpa-onnx in AlgorithVoice:

  encoder.int8.onnx  decoder.onnx  joiner.onnx  tokens.txt

Changes, as CC-BY asks to be stated: the files are the transducer (RNNT)
branch of the same model, exported to ONNX by Algorithco with NeMo, with the
metadata sherpa-onnx reads. The encoder's MatMul weights are quantized to 8
bits; the convolutions, the decoder and the joiner stay in 32-bit float,
because a quantized joiner drops words. Nothing was trained.

Measured on 100 FLEURS uz_uz test recordings: 14.1% word error rate with
these files in AlgorithVoice, against 14.4% for the CTC branch.