Syllabus: LIN313 Language and computers

Course Information

Instructor Contact Information

    • Katrin Erk

    • office hours: Monday, Friday 12:30-1:30, Friday 3-4

    • office: CLA 4.734

    • email: katrin dot erk at mail dot utexas dot edu

Teaching assistant

office hours: Monday 3-4, and Wednesday 1-2, 3-4

Prerequisites

none.

Syllabus and Text

This page serves as the syllabus for this course.

Textbook: Markus Dickinson, Chris Brew, and Detmar Meurers: Language and Computers Wiley-Blackwell (2013)

Additional required readings will be made available for download from the course website.

Exams and assignments

There will be one mid-term exam and one final exam. The midterm will consist of the material covered in the first half of the class, and the final will be comprehensive, but with a greater emphasis on the contents covered in the second half of the class.

Assignments will be updated on the assignments page. A tentative schedule for the entire semester is posted on the schedule page. Readings and exercises may change up one week in advance of their due dates.

Given that homeworks and the exams address the material covered in class, good attendance is essential for doing well in this class.

Content overview

In the past decades, the widening use of computers has had a profound influence on the way ordinary people communicate, search and store information. For the overwhelming majority of people and situations, the natural vehicle for such information is natural language. Text and to a lesser extent speech are crucial encoding formats for the information revolution.

In this course, you will be given insight into the fundamentals of how computers are used to represent, process and organize textual and spoken information, as well as tips on how to effectively integrate this knowledge into working practice. We will cover the theory and practice of human language technology. Topics include text encoding, search technology, tools for writing support, machine translation, dialog systems, computer aided language learning and the social context of language technology.

This course uses natural language systems to motivate students to exercise and develop a range of basic skills in formal and computational analysis. The course philosophy is to ground abstract concepts in real world examples. We introduce strings, regular expressions, finite-state and context-free grammars, as well as algorithms defined over these structures and techniques for probing and evaluating systems that rely on these algorithms. The course goes beyond merely subjective evaluation of systems, emphasizing analysis and reasoning to draw and argue for valid conclusions about the design, capabilities and behavior of natural language systems.

Evaluation will be based on the exams, homeworks, and the essay.

Topics include:

    • Storing language on the computer: Text and speech encoding. Writing systems used for language. Representing text on the computer. Digital representations of speech.

    • Classifying text: Is a piece of text about sports, politics, finance, etc? Does a sentence indicate positive or negative sentiment by the speaker/writer toward the thing being discussed? Are statistical techniques better than rule-based ones, or not? When will the techniques fail? How do we measure the performance of such systems?

    • Dialog systems: Eliza and its surprising success in engaging people in conversation. When are dialog systems used, for what purpose? A closer look at the components of a dialog system. Where is what kind of knowledge needed to make it work?

    • Writer’s aids: Spelling and grammar correction What do so-called grammar checkers and spelling correctors do? What do such programs base their advice on? When does it make sense to use such tools and what kind of errors are to be expected?

    • Forensic linguistics: Can computers help spot patterns that can identify who is the actual author of a text or speech segment? How does this play out in court? What kind of evidence is admissible?

    • Machine translation: What do the free internet-based translation services manage to do and where do they fail? For what purposes can automatic machine translation work reliably? What translation support functions can a computer provide? A closer look at what makes machine translation such a hard task. Is it the grammar, the meaning, the culture, all three, or something else?

    • Language and the Internet: How do we react to computers that make use of language? What does it mean for the way we see ourselves? What assumptions do we make about every user of language, be it a human or a machine. How can we identify which Austin, London or Springfield was meant in a written text? How can we identify the time period associated with a text? How can we use such identifications to visualize large corpora? What resources are necessary for doing this?

Course requirements and grading policy

There will be seven assessed assignments, one essay, and two exams.

    • Assignments (42%): A series of seven assessed assignments will be assigned during the semester. The lowest grade will be dropped, so each homework that counts is worth 7%.

    • Essay (15%): A 1000-1500 word essay on a topic dealing with the social implications of computational applications for language.

    • Mid-term Exam (18%): There will be a mid-term exam on October 9 over the material covered in class up to October 4.

    • Final Exam (25%): The final exam will be given during finals week and will cover all course material.

The course will use plus-minus grading, using the following scale:

Attendance is not required, and it is not used as part of determining the grade.

Extension Policy

If you turn in your assignment late and we have not agreed on an extension beforehand, expect points to be deducted. Extensions will be considered on a case-by-case basis. I urge you to let me know if you are in need of an extension, such that we can make sure that you get the time necessary to complete the assignments.

If an extension has not been agreed on beforehand, then for assignments, by default, 5 points (out of 100) will be deducted for lateness, plus an additional 1 point for every 24-hour period beyond 2 that the assignment is late.

Note that there are always some points to be had, even if you turn in your assignment late. So if you would like to know if you should still turn in the assignment even though it is late, the answer is always yes.

Academic Dishonesty Policy

You are encouraged to discuss assignments with classmates. But all written work must be your own. Students caught cheating will automatically fail the course. If in doubt, ask the instructor.

Notice about students with disabilities

The University of Texas at Austin provides upon request appropriate academic accommodations for qualified students with disabilities. Please contact the Division of Diversity and Community Engagement, Services for Students with Disabilities, 471-6259.

Notice about missed work due to religious holy days

A student who misses an examination, work assignment, or other project due to the observance of a religious holy day will be given an opportunity to complete the work missed within a reasonable time after the absence, provided that he or she has properly notified the instructor. It is the policy of the University of Texas at Austin that the student must notify the instructor at least fourteen days prior to the classes scheduled on dates he or she will be absent to observe a religious holy day. For religious holy days that fall within the first two weeks of the semester, the notice should be given on the first day of the semester. The student will not be penalized for these excused absences, but the instructor may appropriately respond if the student fails to complete satisfactorily the missed assignment or examination within a reasonable time after the excused absence.

Emergency Evacuation Policy

Occupants of buildings on The University of Texas at Austin campus are required to evacuate buildings when a fire alarm is activated. Alarm activation or announcement requires exiting and assembling outside. Familiarize yourself with all exit doors of each classroom and building you may occupy. Remember that the nearest exit door may not be the one you used when entering the building. Students requiring assistance in evacuation shall inform their instructor in writing during the first week of class. In the event of an evacuation, follow the instruction of faculty or class instructors. Do not re-enter a building unless given instructions by the following: Austin Fire Department, The University of Texas at Austin Police Department, or Fire Prevention Services office. Information regarding emergency evacuation routes and emergency procedures can be found at http://www.utexas.edu/emergency.