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NVIDIA
Parakeet-TDT_CTC-110M
Model
NVIDIA
NVIDIA
Parakeet-TDT_CTC-110M

Large size version of hybrid Fast Conformer TDT-CTC 114M parameter model trained on larger dataset of 36000 hrs with Punctuation and Capitalization. This model is jointly developed by NVIDIA NeMo and Suno.ai teams.

This model is backed by NVIDIA's Plus Plus (++) Promise
to learn more about the quality of the datasets used to train this model.
FieldResponse
High-level application domain:ASR
Describe the model input and output, e.g. input: streaming speech / file; output: Text with / without capitalization and punctuation.This model accepts 16000 Hz Mono-channel Audio (wav files) as input and provides transcribed speech as a string for a given audio sample as output.
Is this streaming / offline model?Offline
Explain model architecture e.g., encoder-decoder with RNNT loss / Tokenizer …FastConformer is an optimized version of the Conformer model with 8x depthwise-separable convolutional downsampling. The model is trained in a multitask setup with joint TDT and CTC decoder loss.
Number of parameters114M
List the technical limitations of the model.The model is non-streaming and outputs the speech as a string without capitalization and punctuation. Since this model was trained on publicly available speech datasets, performance might degrade for speech with untrained terms.

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