Search Results for "website using python"

Elevenlabs-api is an open-source Java wrapper around the ElevenLabs Voice Synthesis and Cloning Web API. Compiled JARs are available via the Releases tab. To access your ElevenLabs API key, head to the official website, you can view your xi-API-key using the 'Profile' tab on the website. To set up your ElevenLabs API key, you must register it with the ElevenLabsAPI Java API. For any public repository security, you should store your API key in an environment variable, or external from your source code. The most realistic and versatile AI speech software, ever. ...

A Python/Pytorch app for easily synthesizing human voices. If you are using a language other than English you can add it to the app. Firstly, you'll need to find a deep speech model for your language by going to coqui. You'll then need to download the model.pbmm and alphabet.txt files for your language. Requires Windows 10 or Ubuntu 20.04+ operating system, 5GB+ Disk space, and NVIDIA GPU with at least 4GB of memory & driver version 456.38+ (optional).

...It builds on deep-learning based TTS / voice-cloning technology (in the lineage of projects such as Real-Time-Voice-Cloning), but extends it with support for Mandarin Chinese and multiple Chinese speech datasets — broadening its applicability beyond English. The codebase is implemented in Python (with PyTorch) and includes modules for encoder, synthesizer, vocoder, preprocessing, and inference, as well as demo scripts and a web-server interface for easier experimentation or deployment. MockingBird supports both using pretrained models and training your own synthesizer (with custom datasets), giving flexibility for voice-cloning or custom-voice synthesis depending on your needs.

This repository provides synthesized samples, training and evaluation data, source code, and parameters for the paper One Model, Many Languages: Meta-learning for Multilingual Text-to-Speech. It contains an implementation of Tacotron 2 that supports multilingual experiments and that implements different approaches to encoder parameter sharing. It presents a model combining ideas from Learning to speak fluently in a foreign language: Multilingual speech synthesis and cross-language voice...