Top 14 Open Source AI Voice Projects

In recent years, we’ve seen an explosion of new ideas and tools in the artificial intelligence industry. These new AI tools let users create and express themselves like never before. 

The art world was taken by storm with AI art tools like Midjourney and Stable Diffusion. Meanwhile, writing and coding will never be the same, thanks to AI chat tools like ChatGPT. 

In this article

1. Exploring the Possibilities of AI Voice Projects
2. What are NLP, NLU and NLG AI?
3. Natural Language Processing (NLP)
4. Natural Language Understanding (NLU)
5. Natural Language Generation (NLG)
6. Open Source AI Voice Projects
7. Hugging Face
8. Mycroft AI
9. Josh
10. Coqui
11. Mozilla
12. Pandorabots
13. SingularityNET
14. Rasa
15. Uberduck
16. Stability.ai
17. spaCy
18. Jovo
19. Fast.ai
20. Scikit-learn
21. Final Thoughts on Open Source AI Voice Projects

While audio and voice haven’t seen the same spotlight on the news, AI developers are hard at creating AI voice projects indistinguishable from humans. From conversational chatbots to AI vocals on songs, you can create all types of voice and vocal projects with AI. 

The open-source AI community is leading the way and creating some of the best AI voice tools. But, with so many different projects, it’s hard to find the best ones. Today, we’ll cover our picks for the top 14 open-source AI voice projects and learn about how they are paving the way to create voice applications without the need for costly equipment or voice talent.

Exploring the Possibilities of AI Voice Projects

AI voice technology is creating a world where synthetic voices are almost identical to natural human voice and speech. This isn’t a mere concept but a reality that’s unfolding presently. This technology is transforming various sectors by offering the capability to produce realistic AI voices for a wide range of uses, including:

• Virtual assistants
• Audiobooks
• Podcasts
• Voiceovers for videos
• Customer service chatbots
• Accessibility tools for individuals with speech impairments.

The potential of AI-generated voices is limitless when it comes to the most advanced AI voices, AI voice technology and innovative AI-generated voice sound. This is especially true when we consider the possibilities of AI voice generation using the best AI voice generators available.

Incorporating top-notch text-to-speech technologies results in smooth and natural voice-guided user experiences. This technology allows professionals and individual content creators to generate high-quality voiceovers efficiently, eliminating the need for specialized hardware or professional voice actors.

What are NLP, NLU and NLG AI?

NLP, NLU, and NLG are the foundations of AI that allow computers to process, comprehend, and produce human language in a meaningful manner. NLP, or Natural Language Processing, encompasses the interpretation and interaction with human language data by computers. Natural Language Understanding (NLU) steps in to explain how machines understand the intended meaning behind words, taking into account context, semantics and sentiment.

Natural Language Generation (NLG) focuses on generating natural language content from structured data to facilitate effective communication with humans. The Turing Test, conceived by Alan Turing in 1950, serves as a standard for evaluating a machine’s capability to demonstrate intelligent behavior comparable to a human. These elements form the core of AI voice technology, empowering it to revolutionize industries.

Let’s break down each term and explain their differences. 

Natural Language Processing (NLP)

Natural Language Processing (NLP) focuses on studying and developing language between humans and computers. NLP developers create algorithms and techniques that improve a computer’s understanding of human language. This lets the computer interpret and interact more as a human and less as a machine.

NLP plays a fundamental role in AI voice technology. It includes the comprehensive process of computers interpreting and interacting with human language data. The Python programming language provides a multitude of tools and libraries for NLP tasks, housed in the Natural Language Toolkit (NLTK), an open-source suite. NLTK consists of libraries for numerous NLP tasks such as sentence parsing, word segmentation, tokenization and semantic reasoning.

Originally, NLP applications relied on rules and faced challenges with scalability and the increasing amount of textual and voice data. Yet, the emergence of machine learning and deep learning has transformed NLP. Statistical NLP combines algorithms with machine learning and deep learning, automating the extraction, classification and labeling of text and voice data elements and assigning statistical probabilities to their meanings.

Natural Language Understanding (NLU)

Natural Language Understanding (NLU) is a subform of NLP. It is a technology that enables computers to understand the intended meaning behind words, taking into account context, semantics, and sentiment, helping computers understand language the same way a human would. NLU differs from NLP by focusing on the semantic meaning of words in a language. 

The technology excels in developing projects that feature name recognition, role labeling and sentiment analysis. This helps the computer better understand the context of the conversation. Parsing, a fundamental NLU task, involves transforming text into a structured format for computer analysis. NLU technologies prove essential in creating chat and voice bots that can independently converse with humans.

NLU uses algorithms to decipher data, transforming speech into a structured ontology encompassing semantics and pragmatics definitions. It consists of tasks such as intent recognition, which deduces the user’s sentiment and goals from their text input, and entity recognition, which identifies and extracts critical information about entities within messages. NLU can accurately interpret meanings, even in the face of common human language errors like mispronunciations or incorrect word order.

Natural Language Generation (NLG)

Finally, Natural Language Generation, or NLG, is another subfield of NLP. This subfield focuses on developing applications that generate human-like speech and speech patterns. NLG focuses on syntax and semantics while also incorporating style and tone.

NLG covers a variety of applications like chatbots, story generation and data description, using a range of technologies for different facets of the NLG process. Numerous open-source projects contribute to the NLG field, including RNNLG for dialogue system benchmarking, Plato for conversational AI agents and TGen for statistical natural language generation.

NLG uses techniques like template-based, rule-based and machine learning-based systems to generate speech and text for everything from chatbots to automated reports. These tools can be used to enhance NLG capabilities and improve the quality of generated content.

Open Source AI Voice Projects

AI voice is a quickly advancing industry. Every day, new and exciting projects are announced. These projects offer developers a wealth of resources for creating varied voice and vocal applications. By leveraging these open-source projects, developers can innovate and craft sophisticated AI voice solutions that mirror human voices. Today, you can use these projects in everything from websites with voice chatbots to AI-created voiceovers. 

Recent advances in AI voice make it hard to tell the difference between AI and humans. As technology advances, many teams are leading the way. Below are the top 14 open-source AI voice projects currently in development.

Hugging Face

Hugging Face is a tool and platform for developing machine learning and AI projects. With one of the largest user bases, Hugging Face has extensive resources that help developers create impressive AI tools. Its ease of use and huge libraries make Hugging Face one of the fastest-growing AI communities.

The platform provides an array of models for various areas, including text classification, token classification, question answering, zero-shot classification, translation, summarization and text generation. Combined with a text-to-speech tool, you can use Hugging Face to create effective AI voice projects. 

Hugging Face promotes swift progress in machine learning through open-source stacks and code snippets from its libraries. It supports several modalities for AI projects, such as text, image, video, audio and even 3D.

This open-source platform lets users develop and deploy their tools and is currently being used by over 50,000 organizations for AI development.

Mycroft AI

Mycroft AI is an open-source voice platform project making strides in the area of AI voice technology. Its vision, ‘AI for Everyone’, lets you interact with a variety of devices through voice commands. The software is customizable and lets developers design skills based on their specific needs.

Since it’s open source, any developer can freely extend and deploy their version. You can use a variety of devices like smart speakers and smartphones to interact with a range of applications. In addition to providing a local neural text-to-speech engine named mimic3 for quick performance, Mycroft AI also offers a dedicated repository for the development of third-party skills that facilitate sharing and collaboration.

Mycroft AI prides itself on its open-source format, and it actively encourages sharing the project and building better AI voice software and products. 

Josh

Josh.ai lets you control your home through your voice. It uses NLP technologies to access home smart devices through voice and touch commands, making it stand out as an open-source AI voice assistant platform. It delivers a personalized user experience with an array of different voices, accents and responses, all while maintaining user data privacy.

Like Siri, Josh can understand natural commands. You can talk to it like a person, and it can easily understand complex instructions. Josh is making the dream of a futuristic connected home a reality. 

The internet of things is growing, and Josh gives you access to every tool and device in your home. Josh also offers a wide range of AI voice products, including smart speakers and smart home integration systems. 

Josh.ai allows users to tailor their experience by customizing app settings, choosing from a selection of voices, accents and responses, setting up automations and receiving alerts about unusual activities or potential security breaches in their homes.

Coqui

Coqui.ai is an open-source project with an improved natural language processing model. Using the TensorFlow and PyTorch frameworks, Coqui generates AI voices for video games, post-production, dubbing and more. 

Coqui boasts features like voice cloning, generative voices, and voice control. It’s great for creating unique and dramatic voice overs for videos and games. Whether you want to simulate your voice or create a new voice, Coqui is ready for the task. The library of included voices features everything from a grumpy old man to young cheerful student voices. 

The application also gives you precise control of your recording. You can alter flow, sentiment, emotion and more by using the built-in editing tools of Coqui.

This user-friendly platform gives developers a chance to improve and develop new speech and NLP models. The project is actively developed and comes with a roadmap, documentation and community support channels like GitHub Discussions and Discord.

Mozilla

Mozilla, the organization behind the renowned Firefox web browser, is also advancing in the AI voice technology sector with its Common Voice project. This initiative strives to create an AI capable of speaking in a natural, human-like manner. The Common Voice project is built through the collection of a large volume of voice data used to train their AI models.

Mozilla is developing the tool by amassing an extremely large amount of voice data. The Common Voice website lets you donate your voice and validate the voice of others. So far, Mozilla has gathered over 26,000 hours of voice recordings intending to develop an AI that can accurately replicate human tones and rhythms. This initiative attests to the influence of open-source projects in propelling innovation and progress in AI voice technology.

Pandorabots

Pandorabots started as a chatbot for B2C messaging. It’s since grown into one of the leading intelligent conversational tools online. The platform features open-source chatbot libraries for swift development, encompassing the top 10,000 chitchat inputs. They are working on diverse projects, including AI character chatbots, open-source conversational AI and multilingual chatbots. 

Using both natural language understanding (NLU) and natural language generation (NLG), Pandorabots have impressive capabilities compared to other bots. The advanced algorithms let a Pandorabot converse naturally. Developers can broaden the functionality of chatbots by utilizing open-source connectors for APIs or databases, like those for math or weather data.

Since it’s open source, Pandorabots is always improving and expanding. They have a small talk library that boasts a catalog of over 10,000 inputs. Meanwhile, Pandorabots actively encourages developers to use their API to build new and exciting chatbots. It also facilitates the integration of chatbots with real-time animation like Rapport, improving the user’s conversational experience.

SingularityNET

SingularityNET is a decentralized AI platform offering open-source AI tools and services, and one of the biggest decentralized AI marketplaces running on blockchain technology. You can find a growing library of community-created AI algorithms and tools on SingularityNET. 

They’ve developed an AI-driven mobile application named Song/Splitter, which is designed to segregate music and vocals from audio tracks. The Song/Splitter app employs Deezer Spleeter’s AI service and can be downloaded from the Google Play Store.

The site covers all AI tools and libraries you can use freely. There is an AI marketplace, said to be the largest of its kind, where you can find countless tools to create chatbots, train AI models and create voice AI. You can find speech recognition, voice translation, voice synthesis, and other voice-related tools on SingularityNET.

Rasa

Rasa is an open-source framework that helps you and your business improve interactions through conversational AI tools. This platform lets you design and deploy conversational AI chatbots and virtual assistants. Rasa Pro, an extension of Rasa Open Source, includes extra features for analytics, security and observability, catering to enterprise needs.

Rasa is fully modular and encourages users to use different components to create a chatbot that meets their needs. It’s easy to implement messaging apps and voice assistants with Rasa. 

The Rasa community is growing, and you’ll find countless free community-developed apps ready to deploy on your website. You can custom-tailor any of these apps to match your niche. Feel free to create anything from an insurance agent assistant to an IT service desk support desk with Rasa and its tools.

Uberduck

Uberduck is a creative, open-source voice AI platform. Boasting over 5,000 voices, you can use the tools and libraries at Uberduck to create amazing and expressive voice recordings, AI chatbots and other tools. 

It also lets you make music using AI-generated vocals and lyrics or by letting you input your own lyrics, especially with one of their standout features, the rap song tool. Users can choose beats, select from pre-existing voices and create custom voices.

As an open-source AI project, the platform has gained traction on social media and has been used by notable DJs and brands to create AI voice, music and video experiences.

Stability.ai

Stabilty.ai is another open-source initiative making noteworthy contributions to the AI voice technology landscape. It advocates for generative AI technologies and actively encourages developers to create new and interesting AI projects with their tools. With over 20,000 members on the platform, Stability is leading the way in AI.

While most popular for their text-to-image software, Stable Diffusion XL, the team at Stability.ai is hard at work creating a diverse collection of tools. It has initiatives such as Stable Audio for producing music and sound effects using advanced audio diffusion technology, plus medical research AI.

Their Eleuther.AI hosts different AI projects, including voice generation and voice over tools.

spaCy

spaCy is a widely used open-source library for advanced Natural Language Processing (NLP) tasks across multiple languages. Built on Python, the spaCy library supports multiple languages and helps developers build NLP applications that can easily understand and process multilingual text. Introduced in 2015, spaCy has become an industry benchmark in the NLP sector, offering a vast ecosystem with plugins, machine learning stack integration and custom component capabilities.

You can find tools like the text to data, named entity recognition and dependency parsing on their large open-source library. spaCy is an efficient library that lets developers create code quickly and optimizes their projects for performance. Once ready, deploying your new tool using a wide range of Python libraries and frameworks is easy. 

spaCy supports more than 75 languages and includes 84 trained pipelines for 25 languages, encompassing multi-task learning with pre-trained transformers such as BERT. With a community of over 25,000 developers, spaCy is a key player in the open-source AI voice project community.

spaCy provides a reproducible training system for custom pipelines, enabling detailed configuration of training runs without hidden defaults, thereby facilitating experiment re-running and change tracking.

Jovo

Jovo is an open-source framework designed for constructing voice and chat applications across various platforms. It aids in the development of applications for voice and chat platforms, with a focus on durability and speed in the development process. Jovo was built from the ground up to help developers create voice applications that work across several platforms. This feature makes it one of the best options for creating tools for Alexa, Instagram, Facebook Messenger and Google Assistant. 

Jovo excels by giving developers the tools they need to create AI voice tools efficiently. Some key features include a command line interface for project management, flexible routing systems and integration with popular services like AWS Lambda and Dialogflow. 

You’ll also find an active open-source community working with Jovo. The community is actively creating helpful tools that improve a user’s experience. 

Jovo provides a structure that is both reusable and extensible, allowing tailoring to specific use cases and sharing across multiple projects. It includes debugging and unit testing tools such as the Jovo Debugger and Test Suite to assist in creating stable and predictable voice applications.

Fast.ai

Fast.ai is an open-source, deep learning library for Python, which simplifies and speeds up the creation of deep neural networks. The Fast.ai community engages in discussions on the advancements in using deep learning for audio, encompassing speech analysis and classification. You’ll find API-building models, pre-trained AI models and a host of other utilities.

The library’s key features are its usability and accessibility. Fast.ai designed the library from the ground up to make AI and deep learning more accessible. The library also features extensive tutorials and educational resources for new developers. 

If you’re just learning to use voice apps with AI, you’ll find the audio and voice tutorials essential to your learning process. Unofficial audio modules within Fast.ai aim to automate a range of audio processing tasks, including spectrogram generation, signal enhancement and data augmentation. Participants in the Fast.ai forums have actively experimented with a variety of audio applications, from syllable counting to audio classification challenges.

Scikit-learn

Scikit-learn is a popular open-source machine-learning library for Python that offers tools for handling structured data. This open-source project offers a range of tools that help developers work with structured data. Known for its user-friendly nature, the Scikit-learn library makes machine learning accessible for beginner developers.

The libraries include topics like classification, regression, clustering, model selection and preprocessing. There’s also a helpful community of developers helping improve Scikit-learn as they develop new libraries for the project. 

Developers can contribute to Scikit-learn, which has a community focused on improving the project and developing new libraries. Scikit-learn offers an API that can be integrated directly into various applications developers are working on. If you’re not sure where to start, Scikit-learn has a helpful real-world example library that gives you a wide range of practical applications to try.

Final Thoughts on Open Source AI Voice Projects

As you can see, there are many different open-source AI voice projects available today. Their developers and communities are hard at work perfecting a wide range of tools and applications that improve the user experience. 

From virtual assistants to AI-generated rap songs, AI voice projects are improving daily. By leveraging these open-source tools, developers can create innovative and powerful AI voice tools that are indistinguishable from humans. 

What does the future hold for AI? By approaching AI with care and intentionality, we can work towards a future where AI benefits everyone and enhances our lives in meaningful ways.

Are you a voice actor looking to protect your voice from online theft? Read our blog how to protect your voice IP when working in AI.