Search Results for "human"

The MITRE Annotation Toolkit (MAT) is a suite of tools which can be used for automated and human tagging of annotations. Annotation is a process, used mostly by researchers in natural language processing, of enhancing documents with information about the various phrase types the documents contain. MAT supports both UI interaction and command-line interaction, and provides various levels of control over the overall annotation process.

...Developed by The Natural Language Processing Group at Stanford University, a team of faculty, postdocs, programmers and students who work together on algorithms that allow computers to process and understand human languages. Our work ranges from basic research in computational linguistics to key applications in human language technology, and covers areas such as sentence understanding, automatic question answering, machine translation, syntactic parsing and tagging, sentiment analysis.

This project concerns the development of human language technology resources, based on the approach to share or recycle resources between closely related language. http://gerhard.pro/closely-related-languages/

...Can be used for general purpose by others as well. This translator desktop app uses google translator to translate English text. The auto generated translations are then enriched with human alternation using an easy graphical user interface. Time stamp information may be synched and a subtitle file or a simple textual output may be generated. Additionally it is planned to use google voice tools to also add voice over from these translated text. Finally the subtitle, translated audio (if any) would be muxed with the original video and uploaded.

This is a software of Arabic diacritical marks restoration. It is based mainly on deep architectures using deep neural network. The algorithm generates diacritized text with determined end case. The algorithm is described in detail in: Ilyes Rebai, and Yassine BenAyed 'Text-to-speech synthesis system with Arabic diacritic recognition system', Computer Speech & Language, 2015. We appreciate it very much if you can cite our related work. ************** Installation...

WARNING: There are too many false-positives! This is Alpha release, expect many things to improve, including the algorithms. PLEASE GO TO BROWSE ALL FILES TO READ A FULL DESCRIPTION. The goal of this project is simple: Input two sentences of the same language, and obtain the number (from 0 to 1) denoting the similarity between the inputted sentences, according to semantic categories. This project models my previous...