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NVIDIA AI Enterprise
NVIDIA AI Enterprise
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  • Displaying 12 results
    The large version (114M) of the Multilingual speech recognition model with a FastConformer encoder and a Hybrid decoder (joint RNNT-CTC loss). The model has a vocab size of 2560 and emits text with punctuation and capitalization.
    Model
    Base German 4-gram LM
    Model
    This collection contains two models: 1) FastPitch (around 50M parameters) trained on OpenSLR neutral German dataset with over 23 hours of German speech and 1 speaker. 2) HiFi-GAN trained on mel spectrograms produced by the FastPitch model in (1).
    Model
    German Citrinet ASR model trained on RIVA ASR set
    Model
    English / Spanish / French / German speech recognition model with a FastConformer large (114M) encoder and a Hybrid decoder (joint RNNT-CTC loss). The model has a vocab size of 2560 and emits text with punctuation and capitalization.
    Model
    Base German 4-gram LM
      Model
      German Citrinet ASR model trained on ASR set 2.0
        Model
        A 7B SpeechLLM model trained on speech-to-text recognition (ASR), speech-to-text translation (AST) and audio/speech question answering (SpeechQA, AudioQA) data.
        Model
        German Conformer ASR model trained on ASR set 2.0
          Model
          For each word in the input text, the model: 1) predicts a punctuation mark that should follow the word (if any), the model supports commas, periods and question marks) and 2) predicts if the word should be capitalized or not.
            Model
            For each word in the input text, the model: 1) predicts a punctuation mark that should follow the word (if any), the model supports commas, periods and question marks) and 2) predicts if the word should be capitalized or not.
            Model
            A text classification model to classify documents into one of 26 domain classes across 52 languages.
            Model

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