+1 binding

Should be a very interesting project!

On Sat, Jan 30, 2016 at 8:05 PM, Ashish <paliwalash...@gmail.com> wrote:

> + (non-binding)
>
> On Sat, Jan 30, 2016 at 12:00 PM, Mattmann, Chris A (3980)
> <chris.a.mattm...@jpl.nasa.gov> wrote:
> > Hi Everyone,
> >
> > OK the discussion is now completed. Please VOTE to accept Joshua
> > into the Apache Incubator. I’ll leave the VOTE open for at least
> > the next 72 hours, with hopes to close it next Friday the 5th of
> > February, 2016.
> >
> > [ ] +1 Accept Joshua as an Apache Incubator podling.
> > [ ] +0 Abstain.
> > [ ] -1 Don’t accept Joshua as an Apache Incubator podling because..
> >
> > Of course, I am +1 on this. Please note VOTEs from Incubator PMC
> > members are binding but all are welcome to VOTE!
> >
> > Cheers,
> > Chris
> >
> > ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
> > Chris Mattmann, Ph.D.
> > Chief Architect
> > Instrument Software and Science Data Systems Section (398)
> > NASA Jet Propulsion Laboratory Pasadena, CA 91109 USA
> > Office: 168-519, Mailstop: 168-527
> > Email: chris.a.mattm...@nasa.gov
> > WWW:  http://sunset.usc.edu/~mattmann/
> > ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
> > Adjunct Associate Professor, Computer Science Department
> > University of Southern California, Los Angeles, CA 90089 USA
> > ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
> >
> >
> >
> >
> >
> > -----Original Message-----
> > From: jpluser <chris.a.mattm...@jpl.nasa.gov>
> > Date: Tuesday, January 12, 2016 at 10:56 PM
> > To: "general@incubator.apache.org" <general@incubator.apache.org>
> > Cc: "p...@cs.jhu.edu" <p...@cs.jhu.edu>
> > Subject: [DISCUSS] Apache Joshua Incubator Proposal - Machine Translation
> > Toolkit
> >
> >>Hi Everyone,
> >>
> >>Please find attached for your viewing pleasure a proposed new project,
> >>Apache Joshua, a statistical machine translation toolkit. The proposal
> >>is in wiki draft form at:
> https://wiki.apache.org/incubator/JoshuaProposal
> >>
> >>Proposal text is copied below. I’ll leave the discussion open for a week
> >>and we are interested in folks who would like to be initial committers
> >>and mentors. Please discuss here on the thread.
> >>
> >>Thanks!
> >>
> >>Cheers,
> >>Chris (Champion)
> >>
> >>———
> >>
> >>= Joshua Proposal =
> >>
> >>== Abstract ==
> >>[[joshua-decoder.org|Joshua]] is an open-source statistical machine
> >>translation toolkit. It includes a Java-based decoder for translating
> with
> >>phrase-based, hierarchical, and syntax-based translation models, a
> >>Hadoop-based grammar extractor (Thrax), and an extensive set of tools and
> >>scripts for training and evaluating new models from parallel text.
> >>
> >>== Proposal ==
> >>Joshua is a state of the art statistical machine translation system that
> >>provides a number of features:
> >>
> >> * Support for the two main paradigms in statistical machine translation:
> >>phrase-based and hierarchical / syntactic.
> >> * A sparse feature API that makes it easy to add new feature templates
> >>supporting millions of features
> >> * Native implementations of many tuners (MERT, MIRA, PRO, and AdaGrad)
> >> * Support for lattice decoding, allowing upstream NLP tools to expose
> >>their hypothesis space to the MT system
> >> * An efficient representation for models, allowing for quick loading of
> >>multi-gigabyte model files
> >> * Fast decoding speed (on par with Moses and mtplz)
> >> * Language packs — precompiled models that allow the decoder to be run
> as
> >>a black box
> >> * Thrax, a Hadoop-based tool for learning translation models from
> >>parallel text
> >> * A suite of tools for constructing new models for any language pair for
> >>which sufficient training data exists
> >>
> >>== Background and Rationale ==
> >>A number of factors make this a good time for an Apache project focused
> on
> >>machine translation (MT): the quality of MT output (for many language
> >>pairs); the average computing resources available on computers, relative
> >>to the needs of MT systems; and the availability of a number of
> >>high-quality toolkits, together with a large base of researchers working
> >>on them.
> >>
> >>Over the past decade, machine translation (MT; the automatic translation
> >>of one human language to another) has become a reality. The research into
> >>statistical approaches to translation that began in the early nineties,
> >>together with the availability of large amounts of training data, and
> >>better computing infrastructure, have all come together to produce
> >>translations results that are “good enough” for a large set of language
> >>pairs and use cases. Free services like
> >>[[https://www.bing.com/translator|Bing Translator]] and
> >>[[https://translate.google.com|Google Translate]] have made these
> services
> >>available to the average person through direct interfaces and through
> >>tools like browser plugins, and sites across the world with higher
> >>translation needs use them to translate their pages through
> automatically.
> >>
> >>MT does not require the infrastructure of large corporations in order to
> >>produce feasible output. Machine translation can be resource-intensive,
> >>but need not be prohibitively so. Disk and memory usage are mostly a
> >>matter of model size, which for most language pairs is a few gigabytes at
> >>most, at which size models can provide coverage on the order of tens or
> >>even hundreds of thousands of words in the input and output languages.
> The
> >>computational complexity of the algorithms used to search for
> translations
> >>of new sentences are typically linear in the number of words in the input
> >>sentence, making it possible to run a translation engine on a personal
> >>computer.
> >>
> >>The research community has produced many different open source
> translation
> >>projects for a range of programming languages and under a variety of
> >>licenses. These projects include the core “decoder”, which takes a model
> >>and uses it to translate new sentences between the language pair the
> model
> >>was defined for. They also typically include a large set of tools that
> >>enable new models to be built from large sets of example translations
> >>(“parallel data”) and monolingual texts. These toolkits are usually built
> >>to support the agendas of the (largely) academic researchers that build
> >>them: the repeated cycle of building new models, tuning model parameters
> >>against development data, and evaluating them against held-out test data,
> >>using standard metrics for testing the quality of MT output.
> >>
> >>Together, these three factors—the quality of machine translation output,
> >>the feasibility of translating on standard computers, and the
> availability
> >>of tools to build models—make it reasonable for the end users to use MT
> as
> >>a black-box service, and to run it on their personal machine.
> >>
> >>These factors make it a good time for an organization with the status of
> >>the Apache Foundation to host a machine translation project.
> >>
> >>== Current Status ==
> >>Joshua was originally ported from David Chiang’s Python implementation of
> >>Hiero by Zhifei Li, while he was a Ph.D. student at Johns Hopkins
> >>University. The current version is maintained by Matt Post at Johns
> >>Hopkins’ Human Language Technology Center of Excellence. Joshua has made
> >>many releases with a list of over 20 source code tags. The last release
> of
> >>Joshua was 6.0.5 on November 5th, 2015.
> >>
> >>== Meritocracy ==
> >>The current developers are familiar with meritocratic open source
> >>development at Apache. Apache was chosen specifically because we want to
> >>encourage this style of development for the project.
> >>
> >>== Community ==
> >>Joshua is used widely across the world. Perhaps its biggest (known)
> >>research / industrial user is the Amazon research group in Berlin.
> Another
> >>user is the US Army Research Lab. No formal census has been undertaken,
> >>but posts to the Joshua technical support mailing list, along with the
> >>occasional contributions, suggest small research and academic communities
> >>spread across the world, many of them in India.
> >>
> >>During incubation, we will explicitly seek to increase our usage across
> >>the board, including academic research, industry, and other end users
> >>interested in statistical machine translation.
> >>
> >>== Core Developers ==
> >>The current set of core developers is fairly small, having fallen with
> the
> >>graduation from Johns Hopkins of some core student participants. However,
> >>Joshua is used fairly widely, as mentioned above, and there remains a
> >>commitment from the principal researcher at Johns Hopkins to continue to
> >>use and develop it. Joshua has seen a number of new community members
> >>become interested recently due to a potential for its projected use in a
> >>number of ongoing DARPA projects such as XDATA and Memex.
> >>
> >>== Alignment ==
> >>Joshua is currently Copyright (c) 2015, Johns Hopkins University All
> >>rights reserved and licensed under BSD 2-clause license. It would of
> >>course be the intention to relicense this code under AL2.0 which would
> >>permit expanded and increased use of the software within Apache projects.
> >>There is currently an ongoing effort within the Apache Tika community to
> >>utilize Joshua within Tika’s Translate API, see
> >>[[https://issues.apache.org/jira/browse/TIKA-1343|TIKA-1343]].
> >>
> >>== Known Risks ==
> >>
> >>=== Orphaned products ===
> >>At the moment, regular contributions are made by a single contributor,
> the
> >>lead maintainer. He (Matt Post) plans to continue development for the
> next
> >>few years, but it is still a single point of failure, since the graduate
> >>students who worked on the project have moved on to jobs, mostly in
> >>industry. However, our goal is to help that process by growing the
> >>community in Apache, and at least in growing the community with users and
> >>participants from NASA JPL.
> >>
> >>=== Inexperience with Open Source ===
> >>The team both at Johns Hopkins and NASA JPL have experience with many OSS
> >>software projects at Apache and elsewhere. We understand "how it works"
> >>here at the foundation.
> >>
> >>
> >>== Relationships with Other Apache Products ==
> >>Joshua includes dependences on Hadoop, and also is included as a plugin
> in
> >>Apache Tika. We are also interested in coordinating with other projects
> >>including Spark, and other projects needing MT services for language
> >>translation.
> >>
> >>== Developers ==
> >>Joshua only has one regular developer who is employed by Johns Hopkins
> >>University. NASA JPL (Mattmann and McGibbney) have been contributing
> >>lately including a Brew formula and other contributions to the project
> >>through the DARPA XDATA and Memex programs.
> >>
> >>== Documentation ==
> >>Documentation and publications related to Joshua can be found at
> >>joshua-decoder.org. The source for the Joshua documentation is currently
> >>hosted on Github at
> >>https://github.com/joshua-decoder/joshua-decoder.github.com
> >>
> >>== Initial Source ==
> >>Current source resides at Github: github.com/joshua-decoder/joshua (the
> >>main decoder and toolkit) and github.com/joshua-decoder/thrax (the
> grammar
> >>extraction tool).
> >>
> >>== External Dependencies ==
> >>Joshua has a number of external dependencies. Only BerkeleyLM (Apache
> 2.0)
> >>and KenLM (LGPG 2.1) are run-time decoder dependencies (one of which is
> >>needed for translating sentences with pre-built models). The rest are
> >>dependencies for the build system and pipeline, used for constructing and
> >>training new models from parallel text.
> >>
> >>Apache projects:
> >> * Ant
> >> * Hadoop
> >> * Commons
> >> * Maven
> >> * Ivy
> >>
> >>There are also a number of other open-source projects with various
> >>licenses that the project depends on both dynamically (runtime), and
> >>statically.
> >>
> >>=== GNU GPL 2 ===
> >> * Berkeley Aligner: https://code.google.com/p/berkeleyaligner/
> >>
> >>=== LGPG 2.1 ===
> >> * KenLM: github.com/kpu/kenlm
> >>
> >>=== Apache 2.0 ===
> >> * BerkeleyLM: https://code.google.com/p/berkeleylm/
> >>
> >>=== GNU GPL ===
> >> * GIZA++: http://www.statmt.org/moses/giza/GIZA++.html
> >>
> >>== Required Resources ==
> >> * Mailing Lists
> >>   * priv...@joshua.incubator.apache.org
> >>   * d...@joshua.incubator.apache.org
> >>   * comm...@joshua.incubator.apache.org
> >>
> >> * Git Repos
> >>   * https://git-wip-us.apache.org/repos/asf/joshua.git
> >>
> >> * Issue Tracking
> >>   * JIRA Joshua (JOSHUA)
> >>
> >> * Continuous Integration
> >>   * Jenkins builds on https://builds.apache.org/
> >>
> >> * Web
> >>   * http://joshua.incubator.apache.org/
> >>   * wiki at http://cwiki.apache.org
> >>
> >>== Initial Committers ==
> >>The following is a list of the planned initial Apache committers (the
> >>active subset of the committers for the current repository on Github).
> >>
> >> * Matt Post (p...@cs.jhu.edu)
> >> * Lewis John McGibbney (lewi...@apache.org)
> >> * Chris Mattmann (mattm...@apache.org)
> >>
> >>== Affiliations ==
> >>
> >> * Johns Hopkins University
> >>   * Matt Post
> >>
> >> * NASA JPL
> >>   * Chris Mattmann
> >>   * Lewis John McGibbney
> >>
> >>
> >>== Sponsors ==
> >>=== Champion ===
> >> * Chris Mattmann (NASA/JPL)
> >>
> >>=== Nominated Mentors ===
> >> * Paul Ramirez
> >> * Lewis John McGibbney
> >> * Chris Mattmann
> >>
> >>== Sponsoring Entity ==
> >>The Apache Incubator
> >>
> >>
> >>
> >>
> >>++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
> >>Chris Mattmann, Ph.D.
> >>Chief Architect
> >>Instrument Software and Science Data Systems Section (398)
> >>NASA Jet Propulsion Laboratory Pasadena, CA 91109 USA
> >>Office: 168-519, Mailstop: 168-527
> >>Email: chris.a.mattm...@nasa.gov
> >>WWW:  http://sunset.usc.edu/~mattmann/
> >>++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
> >>Adjunct Associate Professor, Computer Science Department
> >>University of Southern California, Los Angeles, CA 90089 USA
> >>++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
> >>
> >>
> >>
> >
>
>
>
> --
> thanks
> ashish
>
> Blog: http://www.ashishpaliwal.com/blog
> My Photo Galleries: http://www.pbase.com/ashishpaliwal
>
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