Clone a voice in 5 seconds to generate arbitrary speech in real-time
-
Updated
Jul 12, 2020 - Python
Clone a voice in 5 seconds to generate arbitrary speech in real-time
A TensorFlow implementation of Google's Tacotron speech synthesis with pre-trained model (unofficial)
Lingvo
Due to the 2GB contiguous block allocation limitation of 32 bit systems, this line:
https://github.com/readbeyond/aeneas/blob/master/aeneas/audiofile.py#L447
might throw a MemoryError, causing an "unexpected exception".
We should:
Speech synthesis, voice conversion, self-supervised learning, music generation,Automatic Speech Recognition, Speaker Verification, Speech Synthesis, Language Modeling
I'd like to train this model on 8 V100 GPUs - does it support multi GPU training?
Python library and CLI tool to interface with Google Translate's text-to-speech API
After testing this code, I found out that following dependencies must be updated otherwise Exception occurs :
Pytorch > 1.0 # F.one_hot function isn't available in PyTorch v1.0 it requires 1.1 or 1.2
librosa==0.7.0 # for Griffin-Lim -> librosa.feature.inverse introduced in librosa 0.7.0
Also for running soundfile following OS dependency required
sudo apt-get install libsndfile1
It looks like the default initialization scheme with tf.get_variable is uniform Glorot , but the paper uses He's Gaussian.
Final goal is to produce a functional Cboard app for iOS.
We have to use the Cordova repository called ccboard which is already producing the Android app:
https://github.com/cboard-org/ccboard
Unofficial Parallel WaveGAN (+ MelGAN & Multi-band MelGAN) with Pytorch
A Pytorch Implementation of "Neural Speech Synthesis with Transformer Network"
MelGAN vocoder (compatible with NVIDIA/tacotron2)
Android speech recognition and text to speech made easy
An opensource text-to-speech (TTS) voice building tool
Microsoft Text-to-Speech API sample code in several languages, part of Cognitive Services.
A collection of resources to make a smart speaker
This repository has implementation for "Neural Voice Cloning With Few Samples"
Add a description, image, and links to the tts topic page so that developers can more easily learn about it.
To associate your repository with the tts topic, visit your repo's landing page and select "manage topics."
After training, using some script like this: https://github.com/tensorflow/tensorflow/blob/master/tensorflow/python/tools/freeze_graph.py ?
What should be the input node name(s) and output node names used for freeze and inference later?
Thanks!