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Search thousands of GPU-optimized Containers, pretrained Models, SDKs, and Helm charts—ready to accelerate AI, digital twins, and HPC from cloud to edge.
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Accelerate custom generative AI app deployment using pre-built containers with optimized AI models.
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Text to Speech
7
Audio Synthesis
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Text-to-Speech
label: Text-to-Speech
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NVIDIA
Riva TTS English US Auxiliary Files
Contains files used in rmir creation
Model
>3y
Updated
04/04/2023 UTC
NVIDIA
WaveGlow LJS 256 Channels
WaveGlow model weights pre-trained on the LJ Speech dataset to be used with https://github.com/NVIDIA/waveglow.
Conversational AI
DL
+1
Text to Speech
Model
>3y
Updated
04/04/2023 UTC
NVIDIA
Text to Speech Notebook
End to End workflow for text to speech training with TAO Toolkit and deployment using Riva.
Inference
Resource
>3y
Updated
04/04/2023 UTC
NVIDIA
Speech Synthesis English FastPitch
Mel-Spectrogram prediction conditioned on input text with LJSpeech voice.
Model
>2y
Updated
10/06/2023 UTC
NVIDIA
Speech Synthesis HiFi-GAN
GAN-based waveform generator from mel-spectrograms.
Model
>2y
Updated
10/06/2023 UTC
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
>3y
Updated
04/06/2023 UTC
NVIDIA Deep Learning Examples
Tacotron2 PyTorch checkpoint (AMP)
Tacotron2 PyTorch checkpoint trained with AMP
Text to Speech
Model
>3y
Updated
04/04/2023 UTC
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
>3y
Updated
04/04/2023 UTC
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
2d
Updated
08/05/2026 UTC
NVIDIA
Speech Synthesis Waveglow
Universal waveform generator from mel-spectrograms.
Model
>2y
Updated
10/06/2023 UTC
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
>3y
Updated
04/04/2023 UTC
NVIDIA
Speech Synthesis English FastPitch
Mel-Spectrogram prediction conditioned on input text with LJSpeech voice.
Riva
Model
>3y
Updated
04/04/2023 UTC
NVIDIA Deep Learning Examples
Waveglow PyTorch checkpoint
Waveglow PyTorch checkpoint trained with AMP
Text to Speech
Model
>3y
Updated
04/04/2023 UTC
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
Riva
Model
>3y
Updated
04/04/2023 UTC
NVIDIA
Speech Synthesis HiFi-GAN
GAN-based waveform generator from mel-spectrograms.
Riva
Model
>3y
Updated
04/04/2023 UTC
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.
Riva
Model
>3y
Updated
04/04/2023 UTC
Collection
NVIDIA
NeMo - Text to Speech
This collection contains NeMo models for Text to Speech (TTS)
AI
Audio Synthesis
+2
Conversational AI
NeMo
23
Model
16mo
Updated
03/14/2025 UTC
Collection
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
AI
Audio Synthesis
+4
Conversational AI
DL
PyTorch
TensorFlow
2
Container
10
Model
16mo
Updated
03/14/2025 UTC
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