Open Source Java Machine Translation Software for Mac

Stanford Phrasal is a state-of-the-art statistical phrase-based machine translation system, written in Java. At its core, it provides much the same functionality as the core of Moses. Distinctive features include: providing an easy to use API for implementing new decoding model features, the ability to translating using phrases that include gaps (Galley et al. 2010), and conditional extraction of phrase-tables and lexical reordering models. 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.

Translating subtitles in format SubRip from one natural language to other. It is based on Google Translate without API and therefore without payment. Translator have automatic and manual spell checkers.

Distributed phrase-based machine translation training tool based on Hadoop.

Multilingual Content Synchronization with Wikis: CoSyne is a Research and Technological Development project co-funded by the European Union. Details: http://cosyne.eu

Cunei is a data-driven machine translation system that builds dynamic, statistical models based on instances of known translations found in a corpus.

This application was developed by Incentro to satisfy requests by clients for a sentiment analyser for the Dutch language. It is currently in it's alpha stage and we expect to have a beta release by November 2012. If you would like to help with the development or testing of this product please contact us at +31[0]15 76 40 750 - of info {at} incentro.com. Deze applicatie is ontwikkeld door Incentro om te voldoen aan klantaanvragen voor een sentimentanalyse module voor de Nederlandse taal. Momenteel is de module in alpha versie beschikbaar en een beta versie wordt verwacht in november 2012. Als u ons wilt helpen bij het ontwikkelen of testen van deze module, neem dan contact op met Incentro via +31[0]15 76 40 750 - of info {at} incentro.com.

A JAVA Arabic stemmer that is based on Shereen Khoja algorithm. This java class offers a function called stemWrod which takes an arabic word and return the stem of it.

Live Transcribe Speech Engine provides on-device speech recognition components that power real-time transcription for accessibility and everyday voice-first experiences. Its design prioritizes latency and robustness in noisy, far-field environments, enabling continuous transcription with low delay on mobile hardware. The engine manages audio front-end processing—such as noise suppression and voice activity detection—before feeding audio into compact, accurate acoustic and language models. Partial hypotheses stream as words are recognized, then stabilize with minimal jitter as confidence increases, which is crucial for usability. The code emphasizes efficient use of CPU and neural accelerators to balance battery life with responsiveness. Deployed in accessibility contexts, it aims for dependable behavior across accents, environments, and intermittent connectivity, with graceful degradation when resources are constrained.

PRDL is one of the core components within the ENDORSE project. The scope of the language is to encompass clauses from data protection legislation and enterprise privacy policies in order to e.g. derive data access decisions automatically based on the enterprise privacy policies (EPPs). There have been many initiatives for expressing privacy rules and legal restrictions into a computable way. The attempt of PRDL is to present a collaborative result towards a multistakeholder language. The goal was that PRDL should be sufficiently expressive to define EPPs for SMEs, it should link the wording of the data privacy laws of different European countries, and it should be represented in natural language and therefore should be easy to understand. Additionally it should be able to express the workflows that have to be conducted within the helping wizards. After all, it should be automatically or semi automatically executable by a rule engine.

SEPa! Java grammar related class library.

To aid translation of satsangs of Paramhamsa Nithyananda. 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.

Want to count the number of syllables in a word? Want to create a random haiku? This Java application can do both. Just add the JAR file to your project for access to these basic classes. We use CMU's pronunciation dictionary to count each syllable.