General Assembly for Sign Language Interpreters

To all hearing interpreters , sign language enthusiasts, anybody interested to be sign language interpreters; to all deaf interpreters and deaf individuals:

There will be a general assembly meeting for sign language interpreters

Date: 2011 May 21 (Saturday)
Time: 7:30 am - 3:00 pm
Venue:
CAP Development center
7th floor, CAP Building
126 Amorsolo corner VA Rufino
Legaspi Village, Makati

If you are from outside Manila and cannot come to Makati, the assembly will be webcast, e-mail philnasli@yahoo.com to get the instructions. Place in the subject "SLI webcast".

You should have a Yahoo account (http://messenger.yahoo.com/) or a Skype account (http://www.skype.com/intl/en/home) to be able to view the webcast.

Manifold Learning, part 3

Part 1 here
Part 2 here

Non-linear dimensionality reduction

In an earlier post, we saw we can approximate higher dimensional data using dimensionality reduction techniques. However, PCA (and similar methods) have a weakness. It requires the constraints to line along or near straight lines. What about data that lie along curves?

Another Illustrated Example

Let us pretend again we have 2-dimensional data and our tools can only analyse one-dimensional data. We cannot use the trick we used earlier because the data no longer lies close to a straight line. However, we can cheat. Looking at it closely, we can see that our data (almost) lies along a spiral.

Just like before, we are going to use the projections of our data (red circles) onto the spiral as approximations of our data. We can do this as long as our data is "very close" to the spiral.

The final trick is to "unroll" the spiral and pretend it is a straight line. We can now use our tools for analysis. Just like in our previous approximation errors are introduced. As long as the data is "very close" to the spiral, the error introduced is small.

You may also notice that I skipped over how we actually unroll the spiral. We'll discuss one way to do it in the next post.

WiFi on Lenovo Ideapad B450 with Fedora 14

I recently installed Fedora 14 on a Lenovo Ideapad B450 for PDRC and I have had problems with getting the Wi-Fi to work. I am posting this so Google search engines can find it.

The Lenovo Ideapad B450 has an Atheros Gigabit ethernet card and an Atheros AR5001 wifi card. I had installed Fedora 12 on it previously and it worked with no problems. After upgrading it to Fedora 14, the wireless card stopped working. Network Manager in GNOME will have "wireless disabled" and no amount of clicking will enable wifi. After some digging and trial and error I blacklisted the acer-wmi kernel module and wifi was working again.

1. Go to /etc/modprobe.d/
2. Edit blacklist.conf and add the following line: blacklist acer-wmi
3. Reboot!

Deaf denied exit by Bureau of Immigration

UPDATE:
As of 8 am, October 7, 2010, the Bureau of Immigrations under the directive of Under Sec. Jovy Salazar of the Department of Justice has placed Mr. Franklin Corpuz on a Qatar-bound flight this morning. This is to rectify the situation and treatment Mr. Corpuz received on 4 October, 2010. This was made possible thru the appeal of Prof. Raul Pangalangan of the U.P. College of Law. A full investigation is ongoing. Mr. Corpuz intends to file formal legal action against the Immigrations Officer. He STILL needs your support for this.

Please send LETTERS OF PROTEST to:

1. snail mail: Atty. Ronaldo Ledesma
   OIC
   Bureau of Immigrations
   Magallanes Drive, Intramuros
   
2. email (please CC me: ed.cabalfin@gmail.com)
   Dept. Of Justice Action Center
   Attn: Romeo D. Galvez
   dojac@doj.gov.ph
   soj@doj.gov.ph
   
3. by fax: Tel. 521-1614

This is not an official press release. I just want to get this out so more people will know. I'll update this post as soon as I get more information. This is from an email sent by Dr. Martinez of the Philippine Deaf Resource Center (PDRC), edited to include links and notes.

Summary
Name of passenger: Franklin Galano Corpuz
Disability: Deaf
Flight: Bound for Qatar via Qatar Airways QR 645, October 4, 2010; 635a.m.

Documents presented at Immigrations (shall be faxed separately):

1. Affidavit of Support from Al Mana Interiors
2. Detailed Invitation to take part in Business Training
3. Visa paper from Ministry of Interior, State of Qatar
4. Passport with Qatar visa
5. Airplane ticket

Purpose of trip:
Invited by company for Business Training and orientation on program for Persons With Disabilities and eventual employment. Program specifically recruits PWDs, two other Filipinos have been placed in Qatar, one Deaf, the other mobility-challenged(Link)

Highlights of incident:
F. Corpuz arrived at NAIA early 4 October 2010 and checked in. He was accompanied by a Qatar Airways flight attendant to the Immigrations counter. Upon being told by the flight attendant that Mr. Corpuz is Deaf,the Immigrations counter officer directs him to the Bureau of Immigrations Office. He is interviewed there by an Immigrations officer (male) who says that he will be disallowed because he is “deaf and CANNOT SPEAK”. He was then asked to leave the airport.

[PDRC] placed a call to the NAIA Immigrations Office this morning and spoke with Ms. Gladys Castillo and Mr. Jeff Ignacio (administrative staff). They said that as a matter of policy they are not allowed to release the name of the Immigrations Officer who interviewed Mr. Corpuz. Ms. Castillo said to send any letters of complaint to Atty. Ronaldo Ledesma, OIC of Bureau of Immigrations. Mr. Ignacio on the other hand said that in their Indicator Checklist for Offloading, the remarks were as follows: “No sufficient proof that his trip is for business to Qatar considering that he is deaf and mute.” He said that it was not specified as to what proof or documentation was lacking.

Clarification and Correction

I recently got interviewed by loQal about my research. You can read the article here. I guess I didn't explain some things clearly enough and I'd hate to give a false impression regarding the research. Here are some items I'd like to clarify or correct.

• The Filipino Sign Language (FSL) Archive project is a collaboration between:
  1. Philippine Deaf Resource Center (PDRC) - an NGO
  2. Philippine Federation of the Deaf (PFD) - an NGO
  3. Digital Signal Processing (DSP) Lab of the Electrical and Electronics Engineering Institute
  4. Computer Vision and Machine Intelligence Group (CVMIG) of the Department of Computer Science

  DSP and CVMIG are both of the College of Engineering, UP Diliman.

• The FSL Archive Project is a separate project from the Filipino Speech Corpus (PSC) project. For one thing, Sign is not Speech.
• As far as I know, the linguistics research is being done by PDRC and PFD, not UP.
• I don't have an application or system yet that can convert FSL into text. That is a long way off. What I have are experimental programs. Nothing practical. Also; syntax and semantics of FSL is currently poorly understood. Until we get a better handle on that, FSL to text sentences is not possible.
• FSL vs ASL (vs SEE vs MCE). It cannot be denied that American Sign Language (ASL), Manually Coded English (MCE) and Signing Exact English (SEE) has a huge influence on FSL; however, many Filipino Deaf refer to their language as Filipino Sign Language. This is a social, cultural and political issue in addition to a technical issue. For example, the Deaf I met in Cebu called their sign language Cebu Sign Language. And yes, there is a lot of variation between regions, and provinces.
• FSL vs English (vs Tagalog). This one confuses a lot of people. Sign is not Speech. FSL is not English. FSL is not Tagalog. FSL is a separate, distinct language. It helps if you think of Written English as a separate language from Spoken English. There is no equivalent "Written FSL". To facilitate research, signs are assigned a label called a GLOSS. It is a word or phrase borrowed from another language. Since many Deaf in the Philippines have Written English as a second language, the GLOSS is borrowed from Written English. It is often written in ALL CAPS to distinguish it from Written English (example: THINK-SKIP-MIND). Note that while the GLOSS is chosen to be as close to the meaning of the sign as possible, this is not a translation. This is one reason why you sometimes see Tagalog used as a GLOSS (example: LOLA).

I think that covers most of it. If you have more questions, leave a comment. Thanks for reading!

Difficulties in Sign Recognition

What makes it hard to do Sign Recognition? I touched this topic briefly in an earlier post. Simply put, there are a lot of things going on in sign language. In spoken languages, you just have to listen to one thing; in sign language you pay attention to the face, the body, the hands and arms simultaneously.

Another part of the problem is the complexity of sign language itself. Facial expressions, and body posture are part of the language. Some form of facial recognition and expression detection is needed (although I ignore this in my research, a topic for another post). The signs themselves vary when used in a sentence, much like the sounds of words change slightly when spoken in different sentences, and in different contexts.

Variation is another source of problems. Each individual performs the sign differently, similar how different people sound different in spoken languages. Even from the same individual, the signs vary slightly when done at different times. And top it off with regional and local variations of the same sign. This is one reason why I restricted my research to signs used in Metro Manila; if I didn't I'll never finish.

The other source of difficulty is general difficulty of computer vision. How do you tell which is the background vs the foreground? How do you distinguish several people in one image/video? Humans have an incredible ability to figure out faces and postures even when viewing from the side, how do we duplicate this ability in computers? To reduce these issues, I recorded one person signing wearing a plain black shirt in front of a plain black background.

Bibliography

This is a partial dump of the references I have used so far.

• Rafaelito M. Abat and Liza B. Martinez. The history of sign language in the philippines: Piecing together the puzzle. In 9th Philippine Linguistics Congress, Diliman, Quezon City, Philippines, 2006.
• Julius Andrada and Raphael Domingo. Key findings for language planning from the national sign language committee (status report on the use of sign language in the philippines). In 9th Philippine Linguistics Congress, Diliman, Quezon City, Philippines, 2006.
• Yvette S. Apurado and Rommel L. Agravante. The phonology and regional variation of filipino sign language: Considerations for language policy. In 9th Philippine Linguistics Congress, Diliman, Quezon City, Philippines, 2006.
• Robin Battison. Lexical Borrowing in American Sign Language. Linstok Press, Silver Spring, MD, 1978.
• Marie Therese A.P. Bustos and Rowella B. Tanjusay. Filipino sign language in deaf education: Deaf and hearing perspectives. In 9th Philippine Linguistics Congress, Diliman, Quezon City, Philippines, 2006.
• Phil. Deaf Resource Center and Phil. Federation of the Deaf. Part 1: Understanding Structure. An Introduction to Filipino Sign Language. Phil. Deaf Resource Center, 2004.
• Phil. Deaf Resource Center and Phil. Federation of the Deaf. Part 2: Traditional and Emerging Signs. An Introduction to Filipino Sign Language. Phil. Deaf Resource Center, 2004.
• Heeyoul Choi, Brandon Paulson, and Tracy Hammond. Gesture recognition based on manifold learning. Structural, Syntactic, and Statistical Pattern Recognition, 5342:247–256, December 2008.
• Philippe Dreuw, Carol Neidle, Vassilis Athitsos, Stan Sclaroff, and Hermann Ney. Benchmark databases for video-based automatic sign language recognition. In International Conference on Language Resources and Evaluation, Marrakech, Morocco, May 2008. http://www-i6.informatik.rwth-aachen.de/~dreuw/ database.php.
• Raymond G. Gordon Jr., editor. Ethnologue: Languages of the World, 15th ed. SIL International, Dallas, Texas, 2005. http://www.ethnologue.com/.
• Sushmita Mitra and Tinku Acharya. Gesture recognition: A survey. IEEE Trans. Systems, Man & Cybernetics, 37(3):311–323, May 2007.
• Phil. National Statistics Office. Persons with disability comprised 1.23 percent of the total population. Special Release No. 150, March 2005. http://www.census.gov.ph/data/sectordata/sr05150tx.html.
• Sylvie C.W. Ong and Surendra Ranganath. Automatic sign language analysis: A survey and the future beyond lexical meaning. IEEE Trans. Pattern Analysis & Machine Intelligence, 27(6):873–891, June 2005.
• World Health Organization. Deafness and hearing impairment. Fact Sheet N300, March 2006. http://www.who.int/mediacentre/factsheets/fs300/ en/index.html.
• Sam T. Roweis and Lawrence K. Saul. Think globally, fit locally: Unsupervised learning of low dimensional manifolds. Science, 290(5500):2323–2326, December 2000.
• Joshua B. Tenenbaum, Vin de Silva, and John C. Langford. A global geometric framework for nonlinear dimensionality reduction. Science, 290(5500):2319–2323, December 2000. http://waldron.stanford.edu/~isomap/.
• Christian Philipp Vogler. American Sign Language Recognition: Reducing the Complexity of the Task with Phoneme-Based Modeling and Parallel Hidden Markov Models. PhD thesis, University of Pennsylvania, 2003.