Get crystal-clear, human-like voices in seconds with Melo-TTS! A new Open-Source Local TTS

The AI Art
28 Feb 202412:43

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

  • ๐Ÿ“ข The video introduces Melo-TTS, a new open-source local text-to-speech (TTS) model.
  • ๐ŸŽค Melo-TTS is based on Co AI, a TTS engine that can generate high-quality speech with proper training.
  • ๐Ÿš€ A key feature of Melo-TTS is its speed, allowing for real-time conversational speech synthesis.
  • ๐ŸŒ The model is available for testing on the Hugging Face website without any PC requirements other than a web browser.
  • ๐Ÿ”Š Melo-TTS produces speech that, while not at the level of 11 Labs, offers very good quality.
  • ๐ŸŒŸ The system is capable of generating multilingual voices and is planning to include voice training and cloning in future releases.
  • ๐Ÿ“š Users can train their own voices and clone voices, making Melo-TTS highly customizable.
  • ๐Ÿ’ป Melo-TTS can be installed locally on one's machine, providing a personal TTS engine.
  • ๐Ÿ“ฅ The installation process is straightforward and can be done via the Pinocchio platform by downloading and extracting files.
  • ๐Ÿ”ง Melo-TTS requires a significant amount of storage space due to the size of the models and the Python environment it generates.
  • โš™๏ธ After installation, Melo-TTS allows users to synthesize speech with various languages and adjust parameters like speed.
  • ๐Ÿ“ˆ 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

00:00

๐Ÿ˜€ 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.

05:02

๐Ÿ› ๏ธ 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.

10:03

๐Ÿ“ˆ 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

๐Ÿ’กMelo-TTS

Melo-TTS is an open-source local text-to-speech (TTS) model that is capable of generating high-quality, human-like voices quickly. It is based on the Co AI text-to-speech engine and is designed to be fast and efficient, allowing for real-time conversational speech synthesis. In the video, Melo-TTS is showcased for its ability to generate speech rapidly and with good quality, which is a significant feature for applications requiring instant responses.

๐Ÿ’กText-to-Speech (TTS)

Text-to-Speech (TTS) refers to the technology that converts written text into audible speech. It is a crucial component in various applications, such as voice assistants, automated systems, and accessibility tools for the visually impaired. In the context of the video, TTS is the core technology behind Melo-TTS, which is highlighted for its speed and quality in speech generation.

๐Ÿ’กCo AI

Co AI is the underlying text-to-speech engine that Melo-TTS is based on. It is mentioned in the video as providing a model for text-to-speech conversion that can achieve very high-quality results with proper training. Co AI serves as the foundation for Melo-TTS's capabilities and performance.

๐Ÿ’กReal-time conversational speech

Real-time conversational speech is the ability to generate speech that can keep up with natural human conversation speeds. This is important for interactive applications where immediate responses are necessary. The video emphasizes Melo-TTS's speed, making it suitable for real-time speech synthesis.

๐Ÿ’กVoice cloning

Voice cloning is a process where a new voice is created to resemble a specific person's voice. It is one of the future developments planned for Melo-TTS, allowing users to train their own voices. This feature is significant as it can be used for personalized voice responses in various applications.

๐Ÿ’กHugging Face

Hugging Face is a platform where users can run the Melo-TTS model without any requirements on their PC other than a web browser and speakers. It is showcased in the video as a way to easily access and experiment with the Melo-TTS technology.

๐Ÿ’กMultilanguage support

Multilanguage support refers to the ability of a system to function in multiple languages. Melo-TTS is highlighted for being multilanguage, which means it can generate speech in various languages, making it more versatile and useful for a broader audience.

๐Ÿ’กOpen source

Open source describes software where the source code is made available to the public, allowing anyone to view, use, modify, and distribute it. Melo-TTS being open source is a key feature as it enables the community to contribute to its development, use it freely, and customize it to their needs.

๐Ÿ’กPinocchio

Pinocchio is a tool mentioned in the video for installing and managing AI models like Melo-TTS. It simplifies the process of downloading and setting up AI tools, making it more accessible for users who want to experiment with or utilize these technologies.

๐Ÿ’กLocal installation

Local installation refers to the process of installing software or applications directly onto a user's computer or device. In the context of the video, Melo-TTS can be installed locally, allowing users to generate speech without relying on internet connectivity or cloud services.

๐Ÿ’กSpeech synthesis

Speech synthesis is the process of generating human-like speech from text. It is the primary function of Melo-TTS, and the video demonstrates how quickly and efficiently Melo-TTS can synthesize speech, even for lengthy texts.

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.

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