Get crystal-clear, human-like voices in seconds with Melo-TTS! A new Open-Source Local TTS
TLDRThe video introduces Melo-TTS, an open-source local text-to-speech model based on Co AI's text-to-speech engine. It's capable of generating high-quality speech quickly, making it suitable for real-time conversational use. The model's speed is highlighted, with a demonstration showing how it can synthesize a half-minute of speech in just 1.4 seconds. Melo-TTS is also multilingual and promises future updates for voice customization and cloning. The video provides a step-by-step guide on how to install Melo-TTS using Pinocchio, a platform for AI tools, emphasizing its ease of use and the potential for users to train their own voices. The host also notes the need for a significant amount of storage space due to the large size of the models and recommends installing on a separate drive. The video concludes with a demonstration of Melo-TTS synthesizing a long paragraph, showcasing its ability to adjust speech speed and its potential for various applications such as narration and voiceovers.
Takeaways
- π’ The video introduces Melo-TTS, a new open-source local text-to-speech (TTS) model.
- π€ Melo-TTS is based on Co AI, a TTS engine that can generate high-quality speech with proper training.
- π A key feature of Melo-TTS is its speed, allowing for real-time conversational speech synthesis.
- π The model is available for testing on the Hugging Face website without any PC requirements other than a web browser.
- π Melo-TTS produces speech that, while not at the level of 11 Labs, offers very good quality.
- π The system is capable of generating multilingual voices and is planning to include voice training and cloning in future releases.
- π Users can train their own voices and clone voices, making Melo-TTS highly customizable.
- π» Melo-TTS can be installed locally on one's machine, providing a personal TTS engine.
- π₯ The installation process is straightforward and can be done via the Pinocchio platform by downloading and extracting files.
- π§ Melo-TTS requires a significant amount of storage space due to the size of the models and the Python environment it generates.
- βοΈ After installation, Melo-TTS allows users to synthesize speech with various languages and adjust parameters like speed.
- π The text-to-speech field has seen rapid development, and Melo-TTS represents a promising, free-to-use option for generating speech from text.
Q & A
What is Melo-TTS?
-Melo-TTS is a new open-source local text-to-speech (TTS) model that can generate high-quality speech from text. It is based on the Co AI TTS engine and is capable of producing results that can compete with some production-level TTS engines.
What are the key features of Melo-TTS?
-One of the key features of Melo-TTS is its speed, allowing for fast generation of speech which can be implemented in real-time conversational systems. It also offers multilingual support and has plans for future developments including voice cloning and the ability for users to train their own voices.
How does Melo-TTS compare to other TTS engines in terms of quality?
-While Melo-TTS does not reach the level of 11 Labs, which are considered top-tier TTS engines, it provides very good results. The voice quality is high and can be used for applications like notations and voice overs.
How fast can Melo-TTS generate speech?
-Melo-TTS can generate speech incredibly fast. In the demonstration, it took only 1.4 seconds to generate a half-minute of sound from a long text.
Is Melo-TTS available for use on personal computers?
-Yes, Melo-TTS is open-source and can be installed on personal computers. It requires some space as it generates an entire Python environment for the models.
How can users get started with Melo-TTS?
-Users can get started with Melo-TTS by visiting the GitHub page or the Hugging Face page where they can run the model without any requirements other than a web browser and speakers. For local installation, they can download the Pinocchio software, which provides an interface to install and run Melo-TTS.
What are the system requirements for installing Melo-TTS locally?
-To install Melo-TTS locally, users need to have sufficient space on their hard drive or another drive as the installation can require several gigabytes due to the Python environment and model files. Basic software requirements include Cuda and git, and the process may take around half an hour for the first installation.
Can users customize Melo-TTS with their own voices?
-Currently, Melo-TTS offers a handful of voices, but future releases are planned to include training scripts, which will allow users to train their own voices and even perform voice cloning.
How does the installation process of Melo-TTS through Pinocchio work?
-The installation process involves downloading Pinocchio, extracting the files, and running the setup. After the setup, users can discover and install Melo-TTS, which includes downloading required files and python packages. Once installed, a proxy starts, and a link is provided to access the local TTS engine through a web browser.
What is the process like for generating speech with Melo-TTS after the initial installation?
-After the initial installation and model download, generating speech with Melo-TTS is much faster as the models are already loaded. Users can input text and choose to synthesize it in different languages and adjust the speed of the speech.
How does Melo-TTS handle long text inputs for speech generation?
-Melo-TTS can handle long text inputs effectively. After the initial model download, it can synthesize long paragraphs of text into speech rapidly, making it suitable for generating extended content like stories or notations.
What are some potential applications of Melo-TTS?
-Melo-TTS can be used for various applications such as creating voice overs for videos, generating notations, and potentially for real-time speech in conversational systems due to its fast synthesis speed.
Outlines
π Introduction to Mellow TTS and Its Features
The video begins with the host addressing their recent absence due to medical issues and expresses optimism for regular content uploads. The main focus of the video is an introduction to a new text-to-speech model called Mellow TTS, which is based on Co AI. The host praises Mellow TTS for its high-quality speech generation and its impressive speed, which allows for real-time conversational speech. The video provides a demo of the model's capabilities, showcasing its multilingual support and future plans for voice training and cloning. The host also guides viewers on how to access and use the model through the Hugging Face platform, highlighting the ease of use and the model's potential applications in creating notations and voiceovers.
π οΈ Installing Mellow TTS Using Pinocchio
The second paragraph delves into the installation process of Mellow TTS using Pinocchio, a tool that simplifies the process. The host guides viewers through downloading and extracting Pinocchio, and then installing it on their Windows system. The video explains that Pinocchio offers a range of AI tools, but the focus remains on Mellow TTS. The host details the steps to download and install the necessary files and packages for Mellow TTS, noting that the first installation may take a significant amount of time and space due to the size of the required files. The host also advises installing Pinocchio on a separate drive to avoid filling up the system hard drive and concludes the paragraph by showing the final steps to get Mellow TTS up and running locally.
π Local Installation and Usage of Mellow TTS
The final paragraph demonstrates the local installation of Mellow TTS and its usage. After the installation is complete, the host shows how to access the local text-to-speech engine through a browser link provided by Pinocchio. The video highlights that while the first use might be slower due to model downloads, subsequent uses will be faster. The host also provides a long text example to showcase the model's ability to generate speech from longer texts. The video concludes with the host expressing excitement about the rapid development in the text-to-speech field and encouraging viewers to like and subscribe for more content.
Mindmap
Keywords
Melo-TTS
Text-to-Speech (TTS)
Co AI
Real-time conversational speech
Voice cloning
Hugging Face
Multilanguage support
Open source
Pinocchio
Local installation
Speech synthesis
Highlights
Melo-TTS is a new open-source local text-to-speech model that can generate high-quality results with proper training.
Based on Co AI, a text-to-speech engine that provides models for speech synthesis.
The quality of Melo-TTS can compete with production-level text-to-speech engines.
Melo-TTS is notably fast, allowing for real-time conversational speech generation.
The model is multilingual and currently offers a handful of voices, with plans for future expansion.
Users will be able to train their own voices and perform voice cloning in future releases.
The hugging face page allows users to run the model without any PC requirements, just a web browser and speakers.
Melo-TTS can generate speech in 1.4 seconds for a half-minute of text, showcasing its speed.
The voice quality is high, suitable for creating notations and voiceovers.
Different accents, such as British and Hindi, are available for synthesis.
Melo-TTS is open-source and can be installed on personal machines.
Installation is straightforward and can be done via the Pinocchio platform.
The installation process requires significant space due to the size of the downloaded files.
Once installed, Melo-TTS allows for local text-to-speech synthesis with the click of a button.
The field of text-to-speech has seen rapid development, with Melo-TTS being a promising addition.
Users can adjust the speed of the generated speech to their preference.
Melo-TTS provides a local installation option for those who wish to use it without an internet connection.
The first use might take longer due to model downloads, but subsequent uses are faster.