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  • NVIDIA
    Parakeet-TDT_CTC-110M
    Model
    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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