Difference between revisions of "User:OmarKassem"

Revision as of 12:00, 8 April 2019

GSOC 2019 : Light alternative format for all XML files in an Apertium language pair[1]

Personal Details

General Summary

I am Omar Kassem, a senior Computer Engineering Student. I am currently living in Alexandria, Egypt, and I intend to study masters abroad after finishing my undergraduate study. I have some research machine learning and deep learning, and I am currently working on my Graduation Project which is a Deep Learning problem called Visual Question Answering. Last year I started learning more about NLP and I found it interesting. I am currently working on solving a challenge offered by GoogleAI about Gendered Pronoun Resolution which is part of coreference resolution, the task of pairing an expression to its referring entity. This is an important task for natural language.

Contacts

Email : omarahmed1473@outlook.com
LinkedIn : https://www.linkedin.com/in/omarQasim10/
IRC : OmarKassem
Github : https://github.com/omarahmed10
Time zone : GMT+2

Education

I am a senior bachelor student at Alexandria University in Egypt. Recently I have been granted a scholarship to study masters in data science at Innopolis University in Russia.
My undergraduate major is computer engineering, which exposed me to almost everything in computers from the lowest level of zeros and ones to the highest level of HCI (human and computer interaction, mainly deals with user interface).
The subjects I loved the most were artificial intelligence, machine learning, data mining and deep learning, and that's because of the great potential in the AI field that already solved and could solve many of the problems humans face today.

Last Year GSoC

I then applied to classical language tool-kit project (cltk)[2] to enhance Arabic support and adding new functionalities (e.g. Word segmenter, Lemmatization, Part-of-speech tagging, etc.) and that was my proposal[3] but Unfortunately I wasn't accepted in the program. This year I applied only for this one task.

Experience

Industry

Last summer I was a IOS developer intern in InovaEg(company here in Alex). I was working on adding new features for Ummahlink IOS app using Swift programming language.

Online courses

I had taken many online courses in many of the computer engineering tracks. The most remarkable course I finished was udacity's machine-learning nano-degree which is a six-months program and this is the Certificate[4]. In this program I mastered Supervised, Unsupervised, Reinforcement, and Deep Learning fundamentals.

Why interested in apertium ?

As I started being interested in NLP, the best way to explore more and learn in this field is the open source. As in the open source, people from different regions/places contribute and which is the heart of a good machine translation system. Apertium is the best open source project that I have found in the field which is easy to understand and contribute and have very active and supporting contributors.

Project Idea

Coding Challenge

The coding challenge was to set up a pair and train the existing weighted transfer rule code, which I had done several times while testing and debugging the code.
Since I didn't have a coding challenge and also the module was separated from apertium core as mentioned before, Francis Tyers(spectei) told me integrate the module -without the training part- with apertium-transfer, and I did that in this pull-request[5].
Then he told me to make the module depends on libraries already used in apertium and not external ones, as I used 2 libraries pugixml to handle xml files and icu library to handle upper and lower cases, which are not used in apertium. Also Kevin Unhammer(unhammer) gave me some helpful review on the code, and these issues were resolved.

Why google and apertium should sponsor it ?

The improvement in the current language pair and the addition of the new language pair is a continuous process in the Apertium project. The current way of writing the dictionary and the transfer rule is in the format of xml which may be difficult for some developers and make the development difficult and time consuming for them. So, there is need of removing these complexity and providing simple way which will be in text format to write the dictionary and the transfer rules.

How and who will it benefit in society ?

As the project will hopefully enhance apertium translation and make it closer to human translation, apertium will be more reliable and efficient to use in daily life and for document translation, which -in the long term- will enrich the data of languages with data scarcity, and hence help the speakers of such languages enriching and preserving their languages from extinction.

Other ideas ?

I would love to work on "Light alternative format for all XML files in an Apertium language pair"[6] idea along with weighted transfer rules idea too, if there was enough time. As there is an intersection between the two ideas which is the xml transfer files, and since I am already familiar with the documentation of these files, and has written module to handle, match and apply the rules, I think I could design another lighter format than xml, and write converters scripts between the two formats.
I hope in the next few days, I would be to able to finish the coding challenge of this idea so I could be considered working on it too if no other one applied to it.

Work plan

Exams and community bounding

I am having my final exams from May 27 to June 20 and it's almost exactly the same as the first phase of GSoC this year, and since I will not be able to work in my exams duration and even I want at least one free week before the first exam, I will start earlier, even before the announcement of accepted students, and that's because I will continue contribution to the module anyways, if I got accepted or not.
So I will start working on the first phase on April 19 to May 16. And from May 17 to July 20 I will be taking my exams and I will still be able to do minor changes if necessary, and also will be open for discussions and chats about the first phase and the next one, to be ready when I came back to design and implement the code.

Schedule

Pre-GSoC

Week 1 (From April 5 - To April 11)	Continue code reformatting as proposed by mentors.
Week 2 (From April 12 - To May 18)	See what mentors say next to modify in the code. Discuss with them some of the thoughts on the proposed documentation. Begin new refactored module documentation.
Deliverable	Weighted transfer rules module is integrated with apertium-transfer.

First milestone

Week 1 (From April 19 - To April 25)	If code needs further refactoring, bugs/issues fixing, polishing, documentation, etc. Start in it.
Week 2 (From April 26 - To May 2)	Start Designing and Implementing some of the valid thoughts, ideas proposed or discussed with mentors. For now I think sentence splitting is the most promising idea, also may be substituting yasmet with another tool or method.
Week 3 (From May 3 - To May 9)	Continue coding and start testing and debugging.
Week 4 (From May 10 - To May 16)	Finish coding, testing and debugging. Write documentation. Train one chosen pair and evaluate its accuracy.
Deliverable	Hopefully, more accurate, clean and robust weighted transfer rules module.
Week 5 (From June 21 - To June 28)	After exams, I will familiarize myself again with the code because my memory is not good enough :) . Also write the mentor evaluation, complete any unfinished documentation, tests or evaluations, and fix any reported issues or bugs.

Second milestone

Week 5 (From June 28 - To July 4)	Read apertium2 document again, read deprecated or out of date parts from different sources and collect all the up to date transfer files specifications in a new document.
Week 6 (From July 5 - To July 11)	Fix any errors found in the module after collecting the up to date specifications. Update and modify the ambiguous transfer file code to handle both inter- and post-chunk transfer files.
Week 7 (From July 12 - To July 18)	Continue coding and start testing and debugging.
Week 8 (From July 19 - To July 25)	Fix any reported bugs or issues. Finish coding, testing and debugging. Write documentation. Train one chosen pair and evaluate its accuracy. Writing mentor evaluation.
Deliverable	Extended weighted transfer rules module.

Third milestone

Week 9 (From July 26 - To August 1)	Fix any reported bugs or issues on the previous deliverable. Start in a new proposed idea regarding weighted transfer rules or regarding the light weight alternative for xml. If later was chosen, then I will start familiarizing myself with interNOSTRUM-style. Start designing and documenting an interNOSTRUM-style format for at least the transfer rules XML files.
Week 10 (From August 2 - To August 8)	Start writing converters to XML and from XML.
Week 11 (From August 9 - To August 15)	Continue coding. Fix any reported bugs or issues. Finish coding, debugging and testing and comparing results with XML.
Week 12 (From August 16 - To August 19)	Write documentation. Write mentor evaluation.
Deliverable	New light interNOSTRUM-style format that's alternative to XML format, with converters from and to the two formats.

Other summer plans

- For the part-time job, as I was told by Francis that it's not compatible with GSoC, I decided to leave the job by April 15 before the first phase.
- For the first phase of GSoC I will still be in my college, but I will be able to allocate at least 30 hours per week for GSoC.
- For the second and third phases, college will have been finished, and I will be able to allocate at least 40 hours per week for GSoC.

@@ Line 32: / Line 32: @@
 ==== Industry ====
-Last summer I was a IOS developer intern in InovaEg(company here in Alex) <br />
+Last summer I was a IOS developer intern in InovaEg(company here in Alex). I was working on adding new features for Ummahlink IOS app using Swift programming
+language.
@@ Line 42: / Line 43: @@
 === Why interested in apertium ? ===
-As I started being interested in NLP, the best way to explore more and learn in this field is the open source. As in the open source, people from different regions/places contribute and which is the heart of a good machine translation system. Apertium is the best open source project that I have found in the field which is easy to understand and contribute and have very active and supporting contributers.
+As I started being interested in NLP, the best way to explore more and learn in this field is the open source. As in the open source, people from different regions/places contribute and which is the heart of a good machine translation system. Apertium is the best open source project that I have found in the field which is easy to understand and contribute and have very active and supporting contributors.
 == Project Idea ==
-=== Weighted transfer rules ===
-When more than one transfer rule could be applied to a given pattern, we call this ambiguous. Apertium resolve this ambiguity by applying the left-to-right longest match (LRLM) rule, and that is not adequate with all the word/s that follow that pattern/s.<br />
-To enhance this resolution, a new module was introduced to make this ambiguous rules weighted for the word/s that follow the ambiguous pattern, and this is done by training a corpus to generate maximum entropy models that are used to choose the best (highest weight) ambiguous rule to apply.<br />
-The module works as follows:<br />
-- First we train an n-gram -we put n=5- source language model.<br />
-- We split the corpus into sentences, for a given sentence we apply all ambiguous transfer rules for each ambiguous pattern separately from other ambiguous patterns -we apply LRLM rules to them-, and then get score from the n-gram model for each of the ambiguous sentences for that pattern.<br />
-- These scores are then written in some files, each file contains the scores of an ambiguous pattern. These files are considered the datasets for yasmet tool, which trains target language max entropy models.<br />
-- After having the models, the module is now ready for use. By using beam search algorithm we choose the best possible ambiguous rules to apply, hence having the best translation.<br />
-For more detailed explanation you could refer to this documentation[https://docs.google.com/document/d/1t0VnUhw_LwN0oNL7Sk1fqSJyPnWdxYElesuIV_htn7o/edit?usp=sharing].
-=== Weighted transfer rules extension ===
-The weighted transfer module was built to apply only chunker transfer rules. And this idea is to extend that module to be applied to interchunk and postchunk transfer rules too.<br />
-Both of them are similar to the chunker, but with some differences. For example interchunk def-cats will refer to the tags of the chunk itself and not the lexical forms it contains like chunker, and for postchunk they refer to name of the chunk and has nothing to do with tags now. Also chunk element has different use, because it deals with chunks not words. Also there are some differences in clip element attributes between the three transfer files.<br />
-All these differences may be considered minor with respect the whole module that handle the chunker transfer rules. And I think adding these modifications will not take long time.<br />
-So in addition to this extension, I think introducing new ideas or modifications that could enhance the accuracy and efficiency of the whole module could be necessary to do alongside the extension. Also I think I may work in related or not related ideas to this one to make full use of the 3 months period.
-=== Latest updates on WTR module ===
-The module is now finished and in the testing phase. It does well with Kazakh-Turkish pair and we hope it does as well with other pairs like Spanish-English pair which have more transfer rules than any other pair in apertium.<br />
-The latest code is uploaded in this repo[https://github.com/sevilaybayatli/apertium-ambiguous].
-The module is separated from apertium core, that is installing apertium only is not enough as one should download and install our module separately to use it along with apertium.
@@ Line 78: / Line 55: @@
 Since I didn't have a coding challenge and also the module was separated from apertium core as mentioned before, Francis Tyers(spectei) told me integrate the module -without the training part- with apertium-transfer, and I did that in this pull-request[https://github.com/apertium/apertium/pull/41].<br />
 Then he told me to make the module depends on libraries already used in apertium and not external ones, as I used 2 libraries pugixml to handle xml files and icu library to handle upper and lower cases, which are not used in apertium. Also Kevin Unhammer(unhammer) gave me some helpful review on the code, and these issues were resolved.
-=== Additional thoughts ===
-There are additional thoughts and modifications to the weighted transfer rules proposed in the aforementioned documentation[https://docs.google.com/document/d/1t0VnUhw_LwN0oNL7Sk1fqSJyPnWdxYElesuIV_htn7o/edit?usp=sharing].<br />
-And if some of them are valid, They could be applied along with the extension too.
-Also now I am looking for some newer machine or deep learning methods to apply as alternative for yasmet and max entropy method.
 === Why google and apertium should sponsor it ? ===
+The improvement in the current language pair and the addition of the new language pair is a continuous process in the Apertium project. The current way of writing the dictionary and the transfer rule is in the format of xml which may be difficult for some developers and make the development difficult and time consuming for them. So, there is need of removing these complexity and providing simple way which will be in text format to write the dictionary and the transfer rules.
-- The project enhances apertium translation of all pairs making it closer to human translation.<br />
-- I have previous experience and the required qualifications to complete the project successfully. And since I participated in building the module, I will be able to extend it without much difficulty.<br />
-- By being accepted and successful in GSoC program, it would make a huge impact on my cv and hence my career.<br />
-- The stipend and the opportunity to have a job interview with google are huge benefits to a fresh graduate student like me.
@@ Line 261: / Line 228: @@
-[[Category:GSoC 2019 student proposals|Aboelhamd]]
+[[Category:GSoC 2019 student proposals|OmarKassem]]