SEPIA Speech-To-Text Server - Revision history

Florian: optimized format

2021-12-03T10:33:34Z

optimized format

← Older revision		Revision as of 12:33, 3 December 2021
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	* Fast enough to run even on Raspberry Pi 4 (2GB) in real-time (depending on engine and model configuration)		* Fast enough to run even on Raspberry Pi 4 (2GB) in real-time (depending on engine and model configuration)
	* Compatible to [[SEPIA]] Framework client (v0.24+)		* Compatible to [[SEPIA]] Framework client (v0.24+)


	[[Category:STT]]		[[Category:STT]]

Florian: formatting

2021-12-03T10:33:11Z

formatting

← Older revision		Revision as of 12:33, 3 December 2021
Line 14:		Line 14:
	* Fast enough to run even on Raspberry Pi 4 (2GB) in real-time (depending on engine and model configuration)		* Fast enough to run even on Raspberry Pi 4 (2GB) in real-time (depending on engine and model configuration)
	* Compatible to [[SEPIA]] Framework client (v0.24+)		* Compatible to [[SEPIA]] Framework client (v0.24+)

	[[Category:STT]]		[[Category:STT]]

Florian: Created SEPIA STT Server page

2021-12-03T10:26:40Z

Created SEPIA STT Server page

New page

SEPIA Speech-To-Text (STT) Server is a [[wikipedia:WebSocket|WebSocket]] based, full-duplex Python server for real-time automatic speech recognition (ASR) supporting multiple open-source ASR engines. It can receive a stream of audio chunks via the secure WebSocket connection and return transcribed text almost immediately as partial and final results.

One goal of this project is to offer a standardized, secure, real-time interface for all the great open-source ASR tools out there. The server works on all major platforms including single-board devices like Raspberry Pi (4).<ref>https://github.com/SEPIA-Framework/sepia-stt-server</ref>

== Features ==

* WebSocket server ([https://fastapi.tiangolo.com/ Python Fast-API]) that can receive audio streams and send transcribed text at the same time
* Modular architecture to support multiple ASR engines like [[Vosk]] (reference implementation), [[Coqui]], [[Deepspeech]], [[Scribosermo]] and more (under construction)
* Optional post processing of result (e.g. via [https://github.com/allo-media/text2num text2num] and custom modules)
* Standardized API for all engines and support for individual engine features ([[speaker identification]], grammar, confidence score, word timestamps, alternative results, etc.)
* On-the-fly server and engine configuration via HTTP REST API and WebSocket 'welcome' event (including custom grammar, if supported by engine and model)
* User authentication via simple common token or individual tokens for multiple users
* Docker containers with support for all major platform architectures: x86 64Bit (amd64), ARM 32Bit (armv7l) and ARM 64Bit (aarch64)
* Fast enough to run even on Raspberry Pi 4 (2GB) in real-time (depending on engine and model configuration)
* Compatible to [[SEPIA]] Framework client (v0.24+)

[[Category:STT]]