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NVIDIA AI Enterprise
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  • Displaying 18 results
    Contains files used in rmir creation
      Model
      WaveGlow model weights pre-trained on the LJ Speech dataset to be used with https://github.com/NVIDIA/waveglow.
      Model
      End to End workflow for text to speech training with TAO Toolkit and deployment using Riva.
      Resource
      Mel-Spectrogram prediction conditioned on input text with LJSpeech voice.
        Model
        GAN-based waveform generator from mel-spectrograms.
          Model
          NVIDIA Deep Learning Examples
          NVIDIA Deep Learning Examples
          HiFi-GAN for PyTorch
          HiFi-GAN model implements a spectrogram inversion model that allows to synthesize speech waveforms from mel-spectrograms.
            Resource
            NVIDIA Deep Learning Examples
            NVIDIA Deep Learning Examples
            Tacotron2 PyTorch checkpoint (AMP)
            Tacotron2 PyTorch checkpoint trained with AMP
            Model
            NVIDIA Deep Learning Examples
            NVIDIA Deep Learning Examples
            Tacotron2 and Waveglow 2.0 for PyTorch
            The Tacotron 2 and WaveGlow model form a text-to-speech system that enables user to synthesise a natural sounding speech from raw transcripts.
              Resource
              A lightweight native C++ runtime for NVIDIA Nemotron Speech models built on ggml. Runs speech models in real time and batch mode across platforms and backends.
                Container
                Universal waveform generator from mel-spectrograms.
                  Model
                  NVIDIA Deep Learning Examples
                  NVIDIA Deep Learning Examples
                  FastPitch 1.0 for PyTorch
                  The FastPitch model generates mel-spectrograms from raw input text and allows to exert additional control over the synthesized utterances.
                    Resource
                    Mel-Spectrogram prediction conditioned on input text with LJSpeech voice.
                    Model
                    NVIDIA Deep Learning Examples
                    NVIDIA Deep Learning Examples
                    Waveglow PyTorch checkpoint
                    Waveglow PyTorch checkpoint trained with AMP
                    Model
                    FastPitch is a mel-spectrogram generator, designed to be used as the first part of a neural text-to-speech system in conjunction with a neural vocoder
                    Model
                    GAN-based waveform generator from mel-spectrograms.
                    Model
                    HifiGAN is a neural vocoder model for text-to-speech applications. It is intended as the second part of a two-stage speech synthesis pipeline, with a mel-spectrogram generator such as FastPitch as the first stage.
                    Model
                    Collection
                    This collection contains NeMo models for Text to Speech (TTS)
                    23
                    Collection
                    A collection of easy to use, highly optimized Deep Learning Models for Speech Synthesis. Deep Learning Examples provides Data Scientist and Software Engineers with recipes to Train, fine-tune, and deploy State-of-the-Art Models
                    210