NVIDIA FastConformer Hybrid Large (de) img { display: inline; } This model transcribes speech in upper and lower case German alphabet along with spaces, periods, commas, and question marks. It is a "large" version of FastConformer Transducer CTC (around 115M parameters) model. This is a hybrid model trained on two losses: Transducer (default) and CTC. See the model architecture section and NeMo documentation for complete architecture details. NVIDIA NeMo: Training To train, fine tune or play with the model you will need to install NVIDIA NeMo. We recommend you install it after you've installed latest Pytorch version. How to Use this Model The model is available for use in the NeMo toolkit [3], and can be used as a pre trained checkpoint for inference or for fine tuning on another dataset. Automatically instantiate the model Transcribing using Python First, let's get a sample Then simply do: Transcribing many audio files Using Transducer mode inference: Using CTC mode inference: Input This model accepts 16000 Hz Mono channel Audio (wav files) as input. Output This model provides transcribed speech as a string for a given audio sample. Model Architecture FastConformer [1] is an optim…
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