Open source text-to-speech tools have come a long way. Once robotic and choppy, many of today’s TTS engines produce voices that are natural and expressive. Whether you're building an app, reading articles out loud, or setting up an accessibility feature, these tools can get the job done—without the licensing headache. Let’s take a look at some of the most reliable open-source TTS engines you can use today.

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

eSpeak NG

eSpeak NG is lightweight and pretty straightforward. It supports more than 100 languages and works on Windows, macOS, and Linux. What makes it handy is that it’s not a resource hog, so even low-end systems can run it smoothly. Its voice output leans toward robotic, but it’s often used in accessibility tools where speed and clarity matter more than natural tone.

Festival Speech Synthesis System

Festival is one of the oldest names in the open-source TTS space. It’s modular, well-documented, and supports various English dialects. It’s favored in academic environments and lets developers experiment with linguistic models. It also offers both command-line and API interfaces, giving it a broad range of use cases.

Flite (Festival Lite)

Flite is the lighter, faster sibling of Festival. It’s designed for embedded systems and mobile devices. If you're looking for something quick and simple that doesn’t compromise much on quality, Flite is a decent pick. It works well in situations where memory and CPU are limited.

MaryTTS

MaryTTS is Java-based and supports multiple languages. What sets it apart is its flexibility. It allows custom voice creation if you're willing to get into voice building. It has a web-based demo and RESTful API, so integrating it into different applications is pretty seamless. It's often used in research projects due to its extensibility.

Pico TTS

Originally developed by SVOX, Pico TTS is now available as open source. It’s tiny, which makes it ideal for embedded devices. While the voice quality isn't close to neural-level speech, it’s clear enough for basic tasks. It’s often seen in Android systems and IoT projects.

OpenTTS

OpenTTS acts more like a connector. Instead of building its own engine, it provides a framework to work with several TTS engines like eSpeak, Festival, and Flite under one roof. It supports SSML input and makes it easier to switch between backends without rewriting your code.

Mimic

Developed by Mycroft AI, Mimic is focused on privacy and offline performance. It uses voices from CMU’s Arctic database and has a clean API. It's particularly suited for devices where sending audio to external servers isn't an option. It performs decently on small machines like Raspberry Pi.

Mozilla TTS

Mozilla TTS is one of the more advanced open-source options. It uses deep learning models based on Tacotron and WaveRNN, giving it a smoother and more natural voice output. It’s a good fit if you want high-quality speech that feels less synthetic. It also supports training your own models if you have the data and hardware.

Coqui TTS

Coqui is a spin-off of Mozilla TTS, carrying on where Mozilla left off. It’s more active in development and offers pre-trained models for multiple languages. What makes Coqui appealing is its balance between usability and output quality. Developers love it for how easy it is to integrate and tweak.

RHVoice

RHVoice is a lesser-known but solid TTS engine, originally developed for Russian and other Slavic languages. Over time, it has added support for English, Spanish, and others. What sets RHVoice apart is its decent balance between quality and speed, along with low hardware requirements. It works well on desktop systems and mobile platforms, and you’ll often find it used in screen readers and other accessibility tools. The voices it offers aren’t as polished as neural engines like Coqui or Mozilla TTS, but they’re clear and reliable enough for regular use.

Using an Open Source TTS Tool: A Closer Look at Coqui TTS

We’ve listed a bunch of solid options, but let’s narrow our focus to Coqui TTS. If you're looking for a modern, open-source TTS engine that’s beginner-friendly yet powerful, Coqui checks a lot of boxes. In this section, we’ll show how to actually get it running on your own setup.

Start with your environment. Coqui works best in a virtual environment, so open a terminal and create one using Python’s built-in venv. Activate it and install the TTS package using pip. It helps to have Python 3.8 or newer. Once the package is installed, you can check your setup by running the default model to produce a quick voice sample.

To generate audio, use a single command-line instruction. Coqui makes this simple—point to the model, type your sentence, and specify the output location for the WAV file. If you want to adjust the speed or tone of the voice, you can tweak values like speaker_idx or emotion. There’s no need to dive deep into the source code. Most of the control happens through the command line or Python script.

If you're building an app or site, you can load Coqui’s API inside a Python script and process dynamic input. For example, if you’re building a dashboard with alerts, you can pass in variable strings that change based on the event. Since the models are pre-trained, there’s no need to wait hours for setup—you're ready to go in minutes.

Conclusion

Open-source text-to-speech engines are no longer just developer experiments or research tools. Many of them, like Coqui and Mozilla TTS, offer voice output that can compete with commercial services. Others like eSpeak NG or Pico TTS are great when you want speed and simplicity. There’s no single “best” engine—it all depends on what you're after: quality, performance, flexibility, or simplicity. But if you're after a strong mix of ease-of-use and natural sound, Coqui TTS is a great place to start.