Open source TTS models smaller than Kokoro, with voice cloning
The post announces open source text-to-speech models about half the size of Kokoro (82M parameters), with claimed gains in naturalness and accuracy and support for voice cloning. They could lower the cost of running speech synthesis locally.
Source: Modelos TTS open source com metade do tamanho do Kokoro e clonagem de voz (x.com). Text prepared with AI from this source.
What happened and what to do
The post announces open source text-to-speech (TTS) models about half the size of Kokoro, which has 82 million parameters. According to the author, the models score higher on naturalness and accuracy and support voice cloning.
For a company, models of this size can run on its own infrastructure, on modest CPUs or GPUs, reducing the cost per minute of audio and keeping texts and voices away from external services. A typical implementation involves a synthesis service with an internal API, queues for batch generation, access control and consent records for voice cloning, plus a dashboard for latency and cost. Before adopting, it is worth measuring naturalness and response time with the voices and the language your business actually uses.
How the consultancy can help
Diagnosis of where speech synthesis makes sense in your operation, a technical comparison of open source TTS models using your own data and cases, and deployment of a self-hosted voice service with API, access control and cost and latency monitoring on your infrastructure.
Next step
Send a short description of your case, such as voice channels, customer service or audio content, with the estimated volume. We will reply with a scoped proposal for diagnosis and implementation.
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