Multilingual TTS Streaming API

New

Skills

Deep Learning Modeling Monitoring Python websocket

1. Project Overview Objective: Develop a WebSocket-based streaming API layer on top of the existing Kokoro 82M text-to-speech (TTS) engine, enabling real-time audio output as text is received, with minimal latency and robust error handling. Purpose/Goal: Provide low-latency, continuous audio streaming to end-user applications (e.g., web, mobile, IVR systems) via websocket based interface. Ensure that system can handle concurrent client sessions and scalable load without performance degradation. Deliver a well-documented, maintainable codebase. 2. Key Deliverables WebSocket Server Implementation A Python service exposing secure WebSocket endpoints. Ability to accept streaming text input and immediately return synthesized audio chunks as they become available. Architecture should be module so that same can be integrated with Kokoro 82M TTS or any other TTS engine which offer http based API interface Properly call or wrap the Kokoro TTS/any other TTS engine (via API, library, or CLI) within the WebSocket service. Manage session-based text to ensure correct audio output for each client connection. Audio should be stream in PCM or wav format/encoding over WebSocket. Optional fallback or buffer for partially processed audio segments in case of network latency. Ability to handle multiple simultaneous connections without compromising response time or audio quality. Basic load-testing script or instructions for verifying performance under typical and high loads. Authentication & Security Support for secure connections (wss://). Token-based or session-based authentication system to control access. Logging & Monitoring Capture essential logs (e.g., connection events, errors, performance metrics). Documentation README or wiki describing API endpoints, data flows, request/response formats, error handling. Installation, configuration, and deployment instructions. Developer notes on how to extend or customize.

Job Type: Remote

Salary: Not Disclosed

Experience: Expert

Duration: 6 Months

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