Open Source Mac Voice Cloning Software

Simple and powerful voice changer for Linux, written with Python & GTK.

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. Eleven brings the most compelling, rich and lifelike voices to creators and publishers seeking the ultimate tools for storytelling. Generate top-quality spoken audio in any voice and style with the most advanced and multipurpose AI speech tool out there. Our deep learning model renders human intonation and inflections with unprecedented fidelity and adjusts delivery based on context.

PaddleSpeech is an open-source toolkit on PaddlePaddle platform for a variety of critical tasks in speech and audio, with state-of-art and influential models. Via the easy-to-use, efficient, flexible and scalable implementation, our vision is to empower both industrial application and academic research, including training, inference & testing modules, and deployment process. Low barriers to install, CLI, Server, and Streaming Server is available to quick-start your journey. We provide high-speed and ultra-lightweight models, and also cutting-edge technology. We provide production ready streaming asr and streaming tts system. Our frontend contains Text Normalization and Grapheme-to-Phoneme (G2P, including Polyphone and Tone Sandhi). Moreover, we use self-defined linguistic rules to adapt Chinese context.

VoiceSmith makes it possible to train and infer on both single and multispeaker models without any coding experience. It fine-tunes a pretty solid text to speech pipeline based on a modified version of DelightfulTTS and UnivNet on your dataset. Both models were pretrained on a proprietary 5000 speaker dataset. It also provides some tools for dataset preprocessing like automatic text normalization. Windows (only CPU supported currently) or any Linux based operating system. If you want to run this on macOS you have to follow the steps in build from source in order to create the installer. This is untested since I don't currently own a Mac. NVIDIA GPU with CUDA support is highly recommended, you can train on CPU otherwise but it will take days if not weeks. VoiceSmith currently uses a two-stage modified DelightfulTTS and UnivNet pipeline.

singing voice change based on whisper, and lora for singing voice clone. You will feel the beauty of the code from this project. Uni-SVC main branch is for singing voice clone based on whisper with speaker encoder and speaker adapter. Uni-SVC main target is to develop lora for SVC. With lora, maybe clone a singer just need 10 stence after 10 minutes train. Each singer is a plug-in of the base model.

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 cloning, End-to-End Code-Switched TTS with Mix of Monolingual Recordings, and Contextual Parameter Generation for Universal Neural Machine Translation. We provide data for comparison of three multilingual text-to-speech models. The first shares the whole encoder and uses an adversarial classifier to remove speaker-dependent information from the encoder. The second has separate encoders for each language.

VoiceOver is a web application that allows you to transcribe English audio and listen to it in another voice. Choose a source, an audio file (.wav) in English only. Transcribe audio, several algorithms will take care of it. Listen to the generated transcription, a man or a woman, it's up to you!