Speech synthesis, also known as text-to-speech (TTS) synthesis, is a technology that converts written text into spoken words. This tech has a variety of applications including helping those with disabilities, language learning, GPS navigation, and much more. With the advent of open source, numerous text-to-speech synthesis tools have emerged. This article delves into the world of open source voice synthesizers.
Firstly, it's essential to note that not all speech synthesis tools are open source. For instance, while Google Text-to-Speech (TTS) offers a powerful API for developers, it is not open source. Similarly, Amazon Polly, known for providing lifelike voices, is also not open source.
On the other hand, Coqui AI, a high-quality TTS toolkit, is an open source project available on GitHub. It was born out of Mozilla's TTS project and offers a robust command line interface for speech synthesis. Coqui AI certainly has a "voice" – it uses Tacotron2 for voice generation with a focus on creating new voices using a deep learning approach.
The Microsoft Speech Platform, including its text-to-speech capabilities, also isn't open source. However, the Speech API (SAPI5) is provided for developers on Windows platforms.
On the brighter side, the open source domain isn't lacking in speech recognition tools. An excellent example is the CMU Sphinx, a group of speech recognition systems developed at Carnegie Mellon University.
When it comes to high-quality open source tools for voice synthesis, various software stands out:
- eSpeak: A compact open source software speech synthesizer for English and other languages. It runs on Windows, Linux and is suitable for very low-size robot applications.
- Mycroft: An open source voice assistant that uses machine learning to provide text-to-speech and speech recognition features.
- MaryTTS: A flexible, multilingual open source text-to-speech synthesis platform written in Java.
- Mozilla TTS: A deep learning-based text-to-speech engine, which is part of the Common Voice project, aimed at creating a dataset for training voice-enabled apps.
- Festival Speech Synthesis System: Developed by The Centre for Speech Technology Research in the UK, it offers a general framework for building speech synthesis systems and includes a variety of voices.
- Flite (Festival-lite): A lightweight speech synthesis engine based on Festival, suitable for embedded systems and high-volume speech servers.
- HTS: The HMM-Based Speech Synthesis System (HTS) is a system for training and synthesizing speech from text, widely used for its high-quality synthesis capabilities.
- Docker: Although Docker isn't a text-to-speech tool, it's worth noting that many TTS tools like Coqui can be used within Docker, making them portable across platforms.
Each tool brings its pros and cons. Open source voice synthesizers provide a free, customizable, and community-supported platform for developers and end-users. They often come with pre-trained models that allow developers to leverage machine learning and deep learning techniques. However, they may require technical knowledge to set up and use. Moreover, some may lack the quality, consistency, or language support of commercial tools.
As open source continues to disrupt the tech world, voice synthesizers and TTS systems will continue to evolve. They offer immense potential for real-time applications and future development of machine learning, deep learning, and AI in voice recognition and speech synthesis systems.
