kaldi-gstreamer-server | time full-duplex speech recognition server | Speech library
kandi X-RAY | kaldi-gstreamer-server Summary
kandi X-RAY | kaldi-gstreamer-server Summary
This is a real-time full-duplex speech recognition server, based on the Kaldi toolkit and the GStreamer framework and implemented in Python.
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Top functions reviewed by kandi - BETA
- Creates the pipeline
- Render the documentation
- Create the pipeline
- Handle a received message from the server
- Set adaptation state
- Called when a full result is received
- Post processing
- Post post processing
- Process a word
- Called when a result is processed
- Start the client
- Send event to client
- Wait until the decoder has been received
- Finish the request
- Context manager to handle EOS
- Sends the adaptation state to the client
- Called when the connection is closed
- Handle reference text
- Called when an error occurs
- Called when an error occurs
- Stop the worker
- Called when an EOS signal is received
- Start the worker
- Handle EOS signal
- Create a new status listener
- Called when the websocket is closed
kaldi-gstreamer-server Key Features
kaldi-gstreamer-server Examples and Code Snippets
Community Discussions
Trending Discussions on kaldi-gstreamer-server
QUESTION
I'm running the gstreamer server for kaldi, which uses tornado internally to provide an HTTP end-point for transcription, e.g. example.com:8888/dynamic/recognize
I think this is the relevant code:
...ANSWER
Answered 2017-Feb-19 at 01:20Tornado does not have a generic timeout mechanism since it is often used for long-polling and similar requests. The application (in this case, gstreamer) is responsible for managing whatever timeouts it wants to set on its own.
Community Discussions, Code Snippets contain sources that include Stack Exchange Network
Vulnerabilities
No vulnerabilities reported
Install kaldi-gstreamer-server
You can use kaldi-gstreamer-server like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.
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