remsky/Kokoro-FastAPI
Kokoro FastAPI
Kokoro-FastAPI is a text-to-speech API and LLM speech synthesis server that generates spoken audio from text via a REST interface. It functions as a Kubernetes-native deployment designed for orchestrated speech synthesis.
The system includes a voice blending engine that creates unique vocal profiles by mixing multiple existing voices using custom weight ratios.
The service provides real-time audio streaming to reduce latency and generates word-level timestamps for speech synchronization. It manages hardware efficiency through on-demand model loading to optimize VRAM usage and includes system resource monitoring for tracking CPU and GPU states.
Deployment is supported via Helm charts for installation within containerized clusters.
Features
- Text-to-Speech Conversions - Provides a high-quality text-to-speech API for converting written text into spoken audio.
- Text-to-Speech - Functions as a high-fidelity generative synthesis server that converts written text into spoken audio.
- GPU Memory Optimizers - Manages VRAM consumption to prevent exhaustion by dynamically reloading models during request processing.
- Grapheme To Phoneme Conversion - Transforms raw input text into phonetic representations and token IDs before passing them to the synthesis engine.
- Model API Gateways - Exposes the underlying synthesis model and monitoring tools through a FastAPI-based REST gateway.
- Voice Identity Interpolators - Synthesizes unique vocal profiles by interpolating voice embedding vectors based on custom weight ratios.
- Speech Synthesis Services - Serves as a backend synthesis server that transforms text to phonemes and high-fidelity audio.
- Phoneme-Based Speech Processors - Uses a phoneme-based pipeline to convert raw text into phonetic representations for consistent speech synthesis.
- Hybrid Voice Synthesis - Includes a specialized engine for blending multiple speaker characteristics into a unique hybrid voice.
- Synthetic Voice Design - Creates specialized vocal identities by blending multiple existing voices using specific weight ratios.
- VRAM Offloading - Implements VRAM optimization by unloading models to system memory during idle periods.
- Model Weight Offloading - Optimizes GPU memory efficiency by unloading model weights from VRAM during idle periods and reloading them on demand.
- Real-time Synthesis Streaming - Delivers synthesized speech as a continuous audio stream to minimize the time to first byte.
- Response Streaming - Provides real-time audio streaming by sending synthesized speech chunks incrementally to reduce latency.
- OpenAI-Compatible APIs - Implements a standardized external interface for text-to-speech generation compatible with the OpenAI API specification.
- Word-Level Timestamps - Generates precise word-level timing metadata to synchronize spoken audio with on-screen text or animations.
- Speech Synthesis Markup - Provides inline markup tags to control pacing, pauses, and specific pronunciations within synthesized speech.
- Speech Boundary Timestamps - Generates precise word-level timestamps to synchronize spoken audio with text or animations.
- Helm Chart Deployment - Ships predefined Helm charts to automate the deployment and configuration of the synthesis service on Kubernetes.
- Kubernetes Application Deployments - Provides automated workflows for deploying scalable speech synthesis services via Helm charts in Kubernetes.
- AI & Machine Learning - Dockerized text-to-speech wrapper for local models.
Star history
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