FFTNet
by erogol
FFTNet vocoder implementation
AI summary
Text-to-Speech Model
An implementation of a deep learning-based text-to-speech model using the FFTNet architecture.
- stars
- 81
- forks
- 8
- watching
- 15
Similar projects
Found by comparing what the projects do, not just their names.
lifeiteng/vall-e2.1K
Text-to-speech system
A PyTorch implementation of a text-to-speech synthesizer based on large language models
Text-to-Speech Model
A PyTorch implementation of an end-to-end text-to-speech synthesis model.
Machine translation model
A Pytorch implementation of a neural network model for machine translation
awni/speech756
Speech model
A PyTorch implementation of end-to-end speech recognition models.
ConvNet TTS
An implementation of text-to-speech synthesis using convolutional neural networks in PyTorch
Language model trainer
This project provides code and model for improving language understanding through generative pre-training using a transformer-based architecture.
Deep Learning Model
A deep learning model implementation of the DeepLab ResNet architecture for image segmentation tasks.
Language model
An implementation of DeepMind's Relational Recurrent Neural Networks (Santoro et al. 2018) in PyTorch for word language modeling
Communications system
An implementation of a machine learning-based communications system using deep learning techniques.
Segmentation network toolkit
A toolbox for training and evaluating real-time semantic segmentation networks using Torch library.
Speech Transcriber
Enables speech-to-text transcription using a pre-trained Deep Speech model in MATLAB.
CNN model
An implementation of a lightweight convolutional neural network architecture for mobile devices
Audio Model
An audio and speech large language model implementation with pre-trained models, datasets, and inference options
Segmentation model
Custom image segmentation implementation using deep learning with Lua and Torch
taoxugit/attngan1.3K
Text to image generator
Reproduces text-to-image generation with attentional generative adversarial networks.