9 Best Open Source Text-to-Speech (TTS) Engines

Introduction

If you are working on Artificial Intelligence or Machine learning models that require the best Text-to-Speech (TTS), then you are on the right path. Text-to-speech (TTS) technology, especially open source, has changed how we interact with digital content. This technology has come a long way; nowadays, we have access to some incredibly natural-sounding and expressive synthetic voices. While plenty of commercial TTS engines exist, many developers and researchers prefer to work with open-source options, offering more flexibility, transparency, and cost-effectiveness. This article will explore the top 10 open source TTS engines for developers and users.

Understanding Text-to-Speech (TTS) Technology

Text-to-speech (TTS) technology is a form of assistive technology that converts written text into spoken words. This technology has been widely used in various applications, including screen readers, voice assistants, and language translation tools. TTS engines work by processing text input and generating synthetic speech output that resembles human speech.

Importance of Open Source TTS Engines

Open source text-to-speech (TTS) engines promote accessibility, innovation, and transparency in speech synthesis. By being open source, these engines allow developers, researchers, and enthusiasts to access, modify, and distribute the source code freely, fostering a collaborative environment for continuous improvement and customization.

One of the key advantages of open source TTS engines is their potential to enhance accessibility for individuals with disabilities, enabling them to interact with digital content through speech output. Additionally, open source TTS engines encourage innovation by allowing developers to experiment with new techniques, integrate them into existing systems, and contribute their improvements to the community.

Furthermore, the transparency inherent in open source projects promotes trust and scrutiny, ensuring that the underlying algorithms and models are subject to peer review and validation. This openness can lead to identifying and resolving potential biases or vulnerabilities, resulting in more robust and reliable speech synthesis solutions.

Here are the Top 10 Open Source TTS Engines

Mozilla TTS

Mozilla TTS is an open-source text-to-speech engine developed by Mozilla Research. It offers developers a high-quality and customizable text-to-speech solution. Mozilla TTS is a versatile option for various applications supporting multiple languages and voices.

Some key features of Mozilla TTS include:

1. Cross-platform compatibility: Mozilla TTS is designed to work across different operating systems, including Windows, macOS, and Linux, making it widely accessible and versatile.
2. Multilingual support: The engine supports multiple languages, enabling developers to create speech synthesis applications that cater to diverse linguistic needs.
3. High-quality voices: Mozilla TTS employs advanced speech synthesis techniques to generate natural-sounding voices, ensuring a seamless and pleasant user experience.
4. Open source: Mozilla TTS is an open-source project that allows developers to access, modify, and contribute to the codebase, fostering collaboration and innovation within the speech synthesis community.
5. Integration with web technologies: Mozilla TTS is particularly well-suited for integrating web-based applications and services, as it can be easily embedded into web pages using JavaScript.

Mozilla TTS is part of Mozilla’s broader efforts to promote open standards, accessibility, and innovation on the web. By providing an open-source speech synthesis engine, Mozilla aims to empower developers and researchers to create speech-enabled applications and contribute to advancing text-to-speech technologies.

Access Mozilla TTS Github Here

MaryTTS

MaryTTS is a Java-based open source TTS engine that provides natural-sounding speech synthesis. It offers many features, including support for multiple languages, voice customization, and text normalization. MaryTTS is a popular choice among developers for its flexibility and ease of use.

Some key features of MaryTTS include:

1. Multilingual Support: MaryTTS supports multiple languages, including English, German, Russian, Turkish, Telugu, and more.
2. MARY XML and Other Input Formats: It can process input text in MARY XML format as well as plain text, tokenized text, and other formats.
3. Unit Selection and Diphone Voices: It provides unit selection and diphone synthesis voices for some languages.
4. Integration: MaryTTS can be integrated into other Java applications via an API and used in server mode.
5. Voice Import Tool: It includes a voice import tool that allows you to build your own voices from recorded speech data.
6. Open Source: Being open-source, MaryTTS is free to use, modify, and redistribute under the terms of the Lesser GNU Public License (LGPL).

MaryTTS is suitable for various applications requiring text-to-speech capabilities, such as screen readers, e-learning systems, and conversational user interfaces.

Access MaryTTS Github Here

eSpeak

eSpeak is a compact and efficient open source TTS engine that supports multiple languages and voices. It is known for its fast processing speed and clear speech output. eSpeak is a lightweight option for developers looking for a simple and reliable TTS solution.

Some key points about eSpeak:

1. Cross-Platform: It runs on multiple platforms, including Windows, Linux, and macOS.
2. Small Size: The core library is just around 2MB, making it very compact.
3. Multilingual Support: Besides English, eSpeak supports Spanish, Portuguese, French, German, Finnish, and others.
4. Output Formats: Speech output can be produced in WAV format audio files or directly output to the sound device.
5. Text Encodings: eSpeak accepts input text in various encodings like UTF-8, Latin-1, etc.
6. Speech Parameters: Pitch, speed, volume and other parameters of the speech output can be adjusted.
7. Programming Access: Applications can access eSpeak’s functionality through command line tools or programming interfaces like C, C++, Python, etc.
8. SSML Support: It partially supports marking up text input using the SSML markup language.

eSpeak uses formant synthesis technology to produce speech output rather than the common concatenative synthesis used by most modern TTS systems. This makes eSpeak’s voice sound more robotic but allows it to have a very small footprint.

eSpeak is particularly useful for apps that require a small embedded multi-lingual speech engine, like talking clocks, GPS navigation devices, e-book readers, etc.

Access eSpeak TTS Github Here

Festival Speech Synthesis System

Festival is a powerful open source TTS engine with advanced speech synthesis capabilities. It supports multiple languages and voice styles, making it suitable for various applications. Festival is a feature-rich TTS engine that provides high-quality speech output.

Some key points about the Festival:

1. Open Source Framework: Festival provides an extensible multi-lingual framework for building TTS systems from scratch or integrating existing components.
2. Modular Architecture: It has a modular architecture with examples of components like text analysis, linguistic analysis, prosodic modelling, and waveform generation.
3. Multiple APIs: Festival offers several APIs to access its functionality, such as a command line, Scheme command interpreter, C++ library, and Emacs interface.
4. Multilingual Support: While English (US/UK) is the most advanced language, the Festival supports other languages, like Spanish. New components can integrate additional languages.
5. Research Platform: Developed at the University of Edinburgh, Festival serves as a research/teaching platform for exploring new techniques in speech synthesis.
6. Licenses: Earlier versions had a non-commercial use restriction, but current versions use an X11/MIT-style license, allowing free commercial and non-commercial use.
7. Open Standards: It provides support for marking up input text using open XML standards like SABLE for text and APML for pronunciation.

Festival is a powerful open-source toolkit that enables researchers, developers and companies to build customized TTS systems in a modular and extensible manner across multiple languages.

Access Festival TTS Github Here

Flite

Flite is a lightweight and fast open source TTS engine developed by Carnegie Mellon University. It is designed for embedded systems and mobile devices, making it a popular choice for resource-constrained environments. Flite offers clear and natural-sounding speech synthesis for various applications.

Some key points about Flite TTS:

1. Light-weight: Flite is designed to be a small, lightweight engine suitable for embedded systems and devices with limited resources. The entire engine is around 5MB in size.
2. Open Source: Flite is an open source project released under a permissive license allowing free commercial and non-commercial use.
3. Multilingual: While English is the most supported language, Flite provides voices for other languages, such as Spanish, Italian, Romanian, German, and more.
4. Synthesis Technique: It uses concatenative synthesis combined with deterministic unit selection to generate speech output.
5. Input Formats: Flite can process plain text, SSML markup, and its own custom XML format.
6. Programming APIs: It provides C/C++, Python and other programming language APIs for integrating TTS into applications.
7. Multiple Voices: For some languages, like English, multiple voices with varying characteristics (age, gender, etc.) are provided.
8. Fast Performance: Flite aims to maximise CPU execution speed while keeping output intelligibility high.

Flite is suitable for applications needing a small, lightweight and efficient embedded TTS engine that can run on low-resource devices like smartphones, embedded systems, IoT devices, etc. Its open nature allows customization for specific use cases.

Access Flite TTS Github Here

Pico TTS

Pico TTS is a small and efficient open-source TTS engine optimized for mobile devices. It offers high-quality speech synthesis with minimal resource usage, making it ideal for smartphones and tablets. Pico TTS is a reliable option for developers looking for a compact TTS solution. It was formerly known as SVOX Pico, a compact, lightweight, embeddable text-to-speech engine developed by the SVOX company.

Here are some key points about Pico TTS:

1. Small Footprint: One of Pico TTS’s distinguishing features is its very small size. The complete engine is just around 0.5MB, making it suitable for embedded systems.
2. Cross-Platform: It is written in C and can run on multiple platforms/architectures like ARM, x86, MIPS etc.
3. Multilingual: Pico provides voices for several widely spoken languages, including English, German, French, Spanish, and Italian.
4. Open Source: Since being acquired by Nuance, the Pico engine has been open sourced under the Apache 2.0 license.
5. Synthesis Technique: It uses a compact form of concatenative synthesis coupled with prosodic modelling.
6. APIs: C/C++ APIs are provided to integrate Pico into applications and devices.
7. Wake Word Support: Pico supports embedded wake word/hotword detection useful for voice interfaces.
8. Low Resource Usage: It is designed for low memory usage and minimal CPU requirements during runtime.

Pico TTS is optimized for applications and products that require a small TTS engine footprint while retaining reasonable speech quality, such as IoT devices, wearables, embedded systems, or mobile apps where disk space and memory are limited. Its open-source nature also allows customization.

Access Pico TTS Github Here

Mimic

Mimic is a lightweight and fast open source TTS engine developed by Mycroft AI. It offers natural-sounding speech synthesis with support for multiple languages and voices. Mimic is designed for voice assistants and other interactive applications requiring real-time speech output.

Here are some key points about Mimic TTS:

1. Neural TTS: Mimic utilizes neural network models and deep learning for speech synthesis rather than older concatenative or formant synthesis methods. This allows it to produce more natural-sounding speech.
2. Open Source: The engine and pre-trained models are released under an open-source Apache 2.0 license.
3. Multi-Speaker: In addition to standard TTS voices, Mimic can generate audio in the voice style and characteristics of specific speakers by training on that person’s voice data.
4. Low Footprint: Mimic is designed to have a small disk and memory footprint suitable for running on devices like smartphones, IoT hardware etc.
5. Cross-Platform: It supports multiple platforms, including Linux, Windows, and macOS, and can also run in web browsers via WebAssembly.
6. Customizable: Mimic is open-source; developers can retrain their models on custom data to build new voices or fine-tune existing ones.
7. Multi-Lingual: While English is currently the primary focus, Mimic supports other languages, such as Spanish, French, and German, to varying degrees.
8. Integrations: Mimic can be integrated into applications via APIs for programming languages like Python, JavaScript, C++, etc.

Mimic aims to provide an open, customizable, and natural-sounding neural TTS engine that can be embedded into smart devices, voice assistants, audio apps, and other use cases that require low footprint but high-quality speech synthesis.

Access Mimic TTS Github Here

Tacotron 2 (by NVIDIA)

Tacotron is an open-source TTS engine that uses deep learning techniques to generate natural-sounding speech. It offers high-quality speech synthesis with support for expressive and emotional speech styles. Tacotron is a cutting-edge TTS engine suitable for advanced applications. In a nutshell, it is a neural network architecture for speech synthesis developed by Google’s AI research team.

Some key points about Tacotron 2:

1. Neural TTS: It is based on an end-to-end neural network model that directly converts text to speech audio in a single step without requiring additional signal processing components.
2. Sequence-to-Sequence Model: Tacotron 2 uses an encoder-decoder architecture with attention, treating speech synthesis as a sequence-to-sequence problem.
3. Natural Synthesis: It produces highly natural-sounding synthesized speech compared to older concatenative or statistical parametric methods.
4. Speaker Adaptation: The model can be fine-tuned on a new speaker’s voice data to generate audio mimicking that speaker’s vocal characteristics.
5. WaveNet Integration: Tacotron 2 generates mel spectrograms fed to a modified WaveNet model to produce the final time-domain waveform audio.
6. Published Model: Google released a pre-trained Tacotron 2 model for English capable of generating high-quality speech.
7. Open Source: Google has open-sourced the tensorflow implementation of Tacotron 2.
8. Further Extensions: Researchers have built upon Tacotron 2 to create multi-speaker, multi-lingual and other extensions of the base model.

While not a full production-ready system, Tacotron 2 demonstrated significant advances in neural speech synthesis leveraging sequence models. Its open source release enabled further research in highly natural and controllable TTS systems.

Access Tacotron 2 (by NVIDIA) TTS Github Here

ESPnet-TTS

ESPnet-TTS is an open-source text-to-speech (TTS) toolkit developed by Nagoya University and others. It is based on the ESPnet framework, initially designed for speech recognition but extended to support TTS tasks. ESPnet-TTS provides a unified framework for various TTS models and allows researchers to easily train, evaluate, and deploy different TTS models.

Here are some key points about ESPnet-TTS:

1. Part of ESPnet: It is a specialized module within the larger ESPnet (End-to-End Speech Processing Toolkit) framework for speech processing tasks like ASR, ST, VC, etc.
2. End-to-End TTS: ESPnet-TTS implements various end-to-end neural network models for text-to-speech synthesis without relying on traditional concatenative/statistical parametric components.
3. Model Architectures: It implements popular models such as Tacotron 2, Transformer TTS, FastSpeech, ParaNet, and others.
4. Multi-Task Training: The toolkit supports multi-task learning to optimize TTS models for other tasks like speech recognition jointly.
5. Multi-Lingual: While focusing on English initially, it supports building TTS systems for other languages through data augmentation.
6. Open Source: ESPnet-TTS is an open-source toolkit under the Apache 2.0 license on GitHub.
7. Used in Research: Researchers at NICT and other institutions actively use it to develop new TTS techniques and models.

So, in essence, ESPnet-TTS aims to provide an open framework to develop, train, and evaluate state-of-the-art end-to-end neural text-to-speech models leveraging techniques like transfer learning, multi-task optimization, data augmentation, etc., across languages. It complements the broader speech-processing capabilities of the ESPnet toolkit.

Access ESPnet-TTS Github Here

Also read: An end-to-end Guide on Converting Text to Speech and Speech to Text

In-depth Comparison of Text-to-speech Engines

Here is a tabular comparison of the different text-to-speech (TTS) systems:

Conclusion

In conclusion, open source TTS engines are vital in advancing accessibility and innovation in text-to-speech technology. The top 10 open source TTS engines mentioned in this article offer developers and users a wide range of features and capabilities. Whether you are looking for a lightweight TTS engine for mobile devices or a powerful TTS engine for advanced applications, a suitable option is available in the open source community. Explore these TTS engines and unleash the potential of synthetic speech in your projects.

Let us know if we have missed any other open source TTS engines in the comment section.

Pankaj Singh

Hi, I am Pankaj Singh Negi - Senior Content Editor | Passionate about storytelling and crafting compelling narratives that transform ideas into impactful content. I love reading about technology revolutionizing our lifestyle.