Metadata-Version: 1.1
Name: deepspeech-server
Version: 0.3.0
Summary: server for mozilla deepspeech
Home-page: https://github.com/MainRo/deepspeech-server.git
Author: Romain Picard
Author-email: romain.picard@softathome.com
License: MPL-2.0
Description-Content-Type: UNKNOWN
Description: 
        # DeepSpeech Server
        
        This is an http server that can be used to test the mozilla DeepSpeech project.
        You need an environment with DeepSpeech and a model to run this server.
        
        ## Installation
        
        You first need to install deepspeech. Depending on your system you can use the
        CPU package:
        
            pip3 install deepspeech
        
        Or the GPU package:
        
            pip3 install deepspeech-gpu
        
        Then you can install the deepspeech server:
        
            python3 setup.py install   
        
        The server is also available on pypi, so you can install it with pip:    
        
            pip3 install deepspeech-server
        
        
        ## Starting the server
        
            deepspeech-server --config config.json
        
        You can use deepspeech without training a model yourself. Pre-trained
        models are provided by Mozilla in the release page of the project (See the
        download section at the bottom):
        
        https://github.com/mozilla/DeepSpeech/releases
        
        ### Server configuration
        
        The configuration is done with a json file, provided with the "--config" argument.
        Its structure is the following one:
        
            {
              "deepspeech": {
                "model" :"model.pb",
                "alphabet": "alphabet.txt",
                "lm": "lm.binary",
                "trie": "trie"
              }
            }
        
        where:
        
        __model__ is the protobuf model that was generated by deepspeech
        
        __alphabet__ is the alphabet dictionary (as available in the "data" directory of
        the DeepSpeech sources).
        
        __lm__ is the language model.
        
        __trie__ is the trie file.
        
        ## Using the server
        
        Inference on the model is done via http post requests. For example with the
        following curl command:
        
             curl -X POST --data-binary @[myfile.wav] http://localhost:8000/stt
        
Platform: any
Classifier: Development Status :: 3 - Alpha
Classifier: License :: OSI Approved :: Mozilla Public License 2.0 (MPL 2.0)
Classifier: Intended Audience :: Developers
Classifier: Programming Language :: Python :: 3
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
