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MTMonkey – an infrastructure for Machine Translation web services

Typing MT Monkeys

Description

MTMonkey is a simple and easily adaptable infrastructure for Machine Translation web services, written in Python. It allows clients JSON-encoded request for different translation directions to be distributed among multiple MT servers.

MTMonkey Schema

This system consists of:

The communication between the main application server and workers proceeds via XML-RPC requests, but workers accepting JSON requests are also supported on the application server side, allowing alternative worker implementations.

There may be more workers for the same language pair. Workers may run on the same physical machine or on several different machines. For a more detailed description of the overall architecture of MTMonkey, see our paper presented at MT Marathon 2013 in Prague or the accompanying poster.

License

Authors: Aleš Tamchyna, Ondřej Dušek, Rudolf Rosa, Pavel Pecina

Copyright © 2013 Institute of Formal and Applied Linguistics, Charles University in Prague.

Licensed under the Apache License, Version 2.0.

When using this software in your scientific work, please cite the following paper:

Aleš Tamchyna, Ondřej Dušek, Rudolf Rosa, and Pavel Pecina: MTMonkey: A scalable infrastructure for a Machine Translation web service. In Prague Bulletin of Mathematical Linguistics 100, 2013, pp. 31-40.

Contents of this package

Usage

Installation

For installation notes for both workers and the application server, see install/README.md.

API description

For a detailed description of the API used by MTMonkey, see API.md and the paper referenced above.

MTMonkey clients

The package includes command-line and web-based clients that can connect to MTMonkey servers. Please see the respective directories for documentation.

In addition, you can easily send requests to MTMonkey from command-line using the curl tool, or from your browser by typing the correct URL. See the API description for more information.


Acknowledgements

The research leading to these results has received funding from the European Union Seventh Framework Programme (FP7/2007-2013) under grant agreement n° 257528 (KHRESMOI). This work has been using language resources developed and/or stored and/or distributed by the LINDAT-Clarin project of the Ministry of Education of the Czech Republic (project LM2010013). This work has been supported by the AMALACH grant (DF12P01OVV02) of the Ministry of Culture of the Czech Republic.