Machine Translation in Academia and in the Commercial World: a Contrastive Perspective

1. AlonLavie Research Professor – LTI, Carnegie Mellon University Co-founder, President and CTO – Safaba Translation Solutions WMT-2014 June 26, 2014 Machine Translation in Academia and in the Commercial World:a Contrastive Perspective

2. WMT-2014

3. 11-711: Algorithms for NLP LTI Education Committee • Standing LTI Faculty committee mandated to review discuss and propose changes to the LTI education programs and course offerings • Meets about once a month over lunch • Primary activities include: • Reviewing new course proposals from faculty • Assisting with speaker recruitment for the LTI colloquium • Special tasks and projects related to our educational programs • Current members: Bob Frederking, Carolyn Rose, Noah Smith, Alan Black, Eric Nyberg, Teruko Mitamura, Ralf Brown, Alon Lavie

4. LTI Curriculum Review • Special project the committee took upon itself in the fall • Goals: • Develop a more comprehensive understanding of the current state of our curriculum and how it has evolved over the years • Are our current course offerings appropriate and necessary for our graduate programs? • Do we have significant gaps that need to be filled? • Analyze student enrollment in our courses, how it has changed over the years, and draw conclusions • Draw conclusions regarding potential changes in our course offerings, their scheduling, frequency, and/or sequencing • Look at the LTI teaching requirements and salary compensation model and whether it should be tweaked or modified

5. LTI Curriculum Review • So far mostly a fact and information gathering exercise with some limited amount of analysis performed by individual committee members • Three main sub-tasks: • A comparison of our LTI course offerings with similar course offerings at major competing peer institutions. • An analysis of student enrollment data in our courses over the past 15 years. • A basic-level comparison of the teaching requirements and teaching compensation model used across the various departments and units within SCS

6. LTI Curriculum Review • A full report of findings from these three activities was circulated by email yesterday • I will present highlights from the findings • Faculty discussion and guidance: • What other information should we be gathering? • What kinds of analyses would you like to see on this data? • Goal is to come up with some recommendations regarding changes to our courses, our programs and/or our teaching salary compensation model. • Full faculty will get to discuss any proposed changes

7. Comparison of LTI Course Offerings with Peer Institutions • Compiled by Noah Smith and Ralf Brown • Looked at course offerings at Edinburgh, JHU and Stanford and attempted to map these to equivalent courses at LTI/SCS • Departmental structures are somewhat different • Table of LTI courses and their corresponding equivalents • Table of SCS courses typically taken by LTI students and their corresponding equivalents • Table of courses offered by peers that we don’t have

8. Comparison of LTI Course Offerings with Peer Institutions • General Findings: • We are very strong on speech offerings, maybe rivaled by JHU. • We are stronger than these peers in information retrieval offerings. • We are relatively weak on linguistics offerings. • Courses that make the LTI special, compared to this set of peers: • Grammars and lexicons (721) has a “grammar engineering” analogue at Stanford, but is unique in being an LT-oriented introduction to the phenomena of human language. • Machine translation (731) as a full-on course • Structured prediction (763), an advanced statistical NLP course (this course combines two older courses, Language and Statistics 2 (762) and Information Extraction (748)). • Social media analysis (772). • Software engineering courses (791 and 792) that emphasize language technologies. • Inventing future services (794). • Summarization and personal information management (899).

9. Comparison of LTI Course Offerings with Peer Institutions • Obvious ideas for courses offered by peers but not by LTI: • Intro to programming for language technologies, for new MLTs who lack a CS background. This could become a service course for CS masters and PhD students from other applied SCS departments who need to catch up on programming skills quickly. • Bioinformatics. Should discuss with faculty in the Lane Center for Computational Biology. • Cognitive science of language. Should discuss with faculty in Psychology. • Data mining (and text mining); likely of interest to some students in Tepper and Heinz. • Corpus linguistics. Should discuss with Linguistics faculty in Modern Languages, English, and Philosophy.

10. Enrollment Data Analysis • Compiled by Bob Frederking • Based on a spreadsheet generated from a database dump containing every registration for an 11-xxx course since Fall 1996. • There is a line in the spreadsheet for each student in each class each semester, for a total of 7328 raw data points. • Note that this total includes 119xx research registrations and 11700 LTI Colloquium registrations. These have been filtered out of the following charts, except where explicitly shown.

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18. Course Enrollments Total cumulative course enrollments sorted by size

19. Discussion