TTS) technology, also known as
Speech Synthesis, converts text into human-like speech.
The rise of deep learning has led to major advancements in
TTS quality and naturalness, but at the cost of increased
Most big tech companies offer cloud-based
like Google Text-to-Speech , Amazon Polly ,
or Microsoft Text-to-Speech , and new companies
with similar offerings have emerged, such as ElevenLabs , or Coqui Studio .
While convenient, these services require an internet connection, raise privacy concerns, and are prone to network
On-device solutions allow for more flexibility and privacy by synthesizing speech directly on the user's device.
However, few options exist for on-device
TTS. This article explores three open-source Python libraries.
- Install pyTTSx3:
- Save synthesized speech to a file in Python:
While simple to use, eSpeak's voice quality is robotic compared to more modern
- Install Coqui TTS:
- List available models in Python:
- Choose a model name and save synthesized speech to a file:
Coqui offers high-quality voices with natural prosody, at the cost of larger model sizes and longer processing times.
Mimic3 from Mycroft
- Install Mycroft:
- Synthesize speech and save file to directory
For prototyping on-device
TTS, Mimic3 from Mycroft provides a balance of quality and performance.
TTS removes privacy concerns, internet requirements, and minimizes latency. With Python solutions like
PyTTSx3, Coqui TTS, and Mimic3, developers have several options for synthesizing speech directly on devices based on
their needs. However, each solution comes with drawbacks such as poor voice quality, large resource requirements, or
lack of flexible APIs.