We ran out of ElevenLabs credits. This episode introduces our new open-source voices powered by Kokoro, an 82-million parameter text-to-speech model built on StyleTTS 2.
Data flow from text input to audio output, comparing the old cloud-based pipeline to the new local CPU inference.
Kokoro is built on StyleTTS 2, which uses diffusion to generate speech rhythm and intonation. This diagram shows the core components of the 82M parameter model.
Where the 82 million parameters live across model components. Hover to see exact counts.
Real-world generation times for a 60-second audio segment. Kokoro delivers fast CPU-only inference without cloud API overhead.
Operating costs for generating a typical 20-minute episode across different TTS solutions.
Kokoro supports 8 languages with varying levels of phoneme coverage. Click a language to see phoneme distribution.
Why Kokoro needed Docker: misaki-tokenizer requires Python ≤3.12, but the host runs 3.13. This flow shows the solution architecture.
Red cells indicate incompatibility. The misaki-tokenizer + Python 3.13 conflict forced containerization.