Convert PyTorch* QuartzNet Model

NeMo project provides the QuartzNet model.

Download the Pre-Trained QuartzNet Model

To download the pre-trained model, refer to the NeMo Speech Models Catalog. Here are the instructions on how to obtain QuartzNet in ONNX* format.

  1. Install the NeMo toolkit using the instructions.

  2. Run the following code:

import nemo
import nemo.collections.asr as nemo_asr

quartznet = nemo_asr.models.EncDecCTCModel.from_pretrained(model_name="QuartzNet15x5Base-En")
# Export QuartzNet model to ONNX\* format

This code produces 3 ONNX* model files: encoder_qn.onnx, decoder_qn.onnx, qn.onnx. They are decoder, encoder and a combined decoder(encoder(x)) models, respectively.

Convert ONNX* QuartzNet model to IR

If using a combined model:

mo --input_model <MODEL_DIR>/qt.onnx --input_shape [B,64,X]

If using separate models:

mo --input_model <MODEL_DIR>/encoder_qt.onnx --input_shape [B,64,X]
mo --input_model <MODEL_DIR>/decoder_qt.onnx --input_shape [B,1024,Y]

Where shape is determined by the audio file Mel-Spectrogram length: B - batch dimension, X - dimension based on the input length, Y - determined by encoder output, usually X / 2.