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  • Displaying 18 results
    NVIDIA
    NVIDIA
    Riva TTS English US Auxiliary Files
    Contains files used in rmir creation
      Model
      NVIDIA
      NVIDIA
      WaveGlow LJS 256 Channels
      WaveGlow model weights pre-trained on the LJ Speech dataset to be used with https://github.com/NVIDIA/waveglow.
      Model
      NVIDIA
      NVIDIA
      nemo-speech.cpp
      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
        NVIDIA
        NVIDIA
        Text to Speech Notebook
        End to End workflow for text to speech training with TAO Toolkit and deployment using Riva.
        Resource
        NVIDIA
        NVIDIA
        Speech Synthesis English FastPitch
        Mel-Spectrogram prediction conditioned on input text with LJSpeech voice.
          Model
          NVIDIA
          NVIDIA
          Speech Synthesis HiFi-GAN
          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
                NVIDIA
                NVIDIA
                Speech Synthesis Waveglow
                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
                    NVIDIA
                    NVIDIA
                    Speech Synthesis English FastPitch
                    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
                    NVIDIA
                    NVIDIA
                    RIVA EnglishUS Fastpitch
                    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
                    NVIDIA
                    NVIDIA
                    Speech Synthesis HiFi-GAN
                    GAN-based waveform generator from mel-spectrograms.
                    Model
                    NVIDIA
                    NVIDIA
                    RIVA EnglishUS Hifigan
                    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
                    NVIDIA
                    NVIDIA
                    NeMo - Text to Speech
                    This collection contains NeMo models for Text to Speech (TTS)
                    23
                    Collection
                    NVIDIA
                    NVIDIA
                    Speech Synthesis
                    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

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