Home


About
   Directions
   Admissions
   How To Apply
   The LTI Brochure

Education
   Ph.D.
   M.S.
   Undergrad Minor
   Courses
    FYI

LTI Forms

Seminars
   LTI Seminar Series
   Joint Speech Seminar (JSS)
   Machine Translation (MT)
   Student Research Symposium
   Information Retrieval Series

Visitor Information
   General
   Maps & Directions
   Hotel Links
   Parking Information

Research
   Projects
   Reports
    Dissertations

People
   Faculty
   Students
   Upcoming Graduates
   Staff
   Visitors   
   Who to See for What

Contacts


Ph.D. Program in Language and Information Technologies

Objective

The Language Technologies Institute, a world leader in the areas of speech processing, language processing, information retrieval, machine translation, machine learning, and bio-informatics, offers a doctorate program that enables candidates to become world leaders in the field of human language technologies.

The PhD program offers a combination of taught courses and directed research project work, leading to the candidate's own research topic and thesis. Normally, PhD candidates concentrate on courses during the first two years of the program, and increase the time spent on their research topic as the years progress. Candidates are affiliated with an advisor's research project in which they carry out their own research as their interests mature.

The LTI offers a unique opportunity to do more than just advance the state of the art in a single language technologies research area. The breadth of language technologies expertise in the department enables new research in combinations of the core subjects, for example, in speech-to-speech translation, spoken dialog systems, language-based tutoring systems, and question/answering systems.

With our combination of core research and applied research projects, graduates of the PhD program can choose from a variety of possible career paths. Our graduates go to top jobs in industry, both in large industrial research laboratories and in small start-ups that take new research ideas to market; academic careers in the US and the rest of the world; and government laboratories.

The LTI's mix of core computer science, linguistics, statistics, psychology, and biology makes it the ideal place for students to learn their craft and to gain the experience that they need to become world leaders in human language technology and computational biology.

Program Requirements

The Ph.D. in Language and Information Technologies consists of the following components:

  • Successful completion of a set of courses
  • Mastery of certain proficiencies
  • A program of research culminating in a Ph.D. thesis.

    • Course Requirement

    The LTI curriculum was revised in Spring 2001 to eliminate the "core course" concept. See the LTI Handbook.

    The course requirement consists of eight (8) courses from the list of LTI core courses. Students should select specific courses in consultation with their advisor, keeping in mind that not all courses are offered each year. (Each 6-unit lab course counts as one half of a course towards the total eight required.)

    Upon completion of the eight required courses, students may, at their option, take additional courses as electives. Students may select additional courses from the LTI list, or related courses from the Computer Science Department, or other CMU or Pitt departments. Students interested in speech should consider speech-oriented electives; other areas of interest include Linguistics, Statistics, and Human-Computer Interaction (HCI).

    When selecting the eight required courses and electives, at least one course must be selected from each focus area listed here.

    All students must also enroll for a minimum of two sections in the Language Engineering laboratory, which includes hands-on work in four different laboratory modules (Speech, Machine Translation, Information Retrieval, Natural Language Analysis). The lab modules are self paced, with TA and faculty guidance. (As mentioned above, each lab counts as one half of a course towards the total eight required.)

    Course Descriptions

    An up-to-date course list with descriptions is available here.

    Model Curriculum

    The following gives a possible Ph.D. curriculum for a student specializing in Machine Translation. Specializations in Speech, Information Retrieval, and Multimedia Systems will be similar in structure, with appropriate course substitutions.

    THIS IS ONLY AN EXAMPLE CURRICULUM! It is not meant to apply to every case, or even most cases.

    Semester I Semester II
    Year 1
    Grammars and Lexicons
    Algorithms for NLP
    Research
    Machine Translation
    Artificial Intelligence
    Research
    Year 2
    Software Engineering for LT (I)
    Machine Learning
    Research
    Software Engineering for LT (II)
    Language and Statistics
    Research
    Year 3
    Teaching (TA)
    Self-Paced Lab
    Research
    Thesis Proposal
    Self-Paced Lab
    Research
    Year 4
    Elective or Seminar
    Research
    Elective or Seminar
    Research
    Year 5
    Research
    Thesis Defense

    Proficiencies

    The following skills must be demonstrated in the course of graduate study, with flexibility in the form and timing of their demonstration:

    Writing
    Satisfied via a conference paper or article that has passed peer review, or via a longer internal paper or report reviewed by several faculty. The topic of the paper may be the student's research results, a comprehensive survey of a research area, a linguistic analysis paper, or any other pertinent topic.

    Presentation
    Satisfied via a public presentation of reasonable quality, such as an external conference presentation or an internal seminar presentation reviewed by several faculty.

    Programming
    Normally the programming requirement will be satisfied in the course of a student's research and/or project work, but could also be satisfied via explicit apprenticeship if desired.

    Teaching
    Satisfied by assisting in the teaching of two classes (i.e. being a TA for two semesters) including the planning of a portion of the syllabus, exercises and delivery of some of the lectures under faculty supervision.

    Research and Ph.D. Thesis

    It is expected that all Ph.D. students engage in active research from their first semester. Moreover, advisor selection occurs in the first month of entering the Ph.D. program, with the option to change at a later time. Roughly half of a student's time should be allocated to research and lab work, and half to courses until these are completed.

    The dissertation proposal, normally presented at the end of the third year, should be a document specifying:

  • The general area of investigation, and the specific problem(s) addressed.
  • A clear argument for the significance of this problem, and the expected scientific contributions in the proposed work towards its solution.
  • Relevant past and on-going research, including competing approaches.
  • Description of work to date to establish a measure of credibility with respect to the proposed research, including any preliminary results.
  • Description of work remaining to be done, including theoretical framework, and/or system building and/or experimentation and evaluation metrics.
  • A projected timeline for completion.

    • A dissertation committee consisting of the advisor, at least two other CMU faculty in language technologies, and at least one external member should be approved prior to the proposal. Note: University rules require that the time and place of the proposal presentation be publically announced at least one week prior to the presentation. This should be coordinated with the Chair of the Graduate Programs.

    The dissertation itself, normally completed during the fifth year, should include a detailed description of all the work done, including its clear evaluation and the final scientific contributions. There are no fixed style or document length guidelines or requirements. The dissertation defense is a public presentation and defense of the dissertation results. Note: University rules again require that the time and place of the dissertation defense be publically announced at least one week prior to the defense. This should also be coordinated with the Chair of the Graduate Programs.

    Financial Support

    Whereas all Ph.D. students will receive financial support, the exact form of that support may vary. Possible forms of support include external fellowships, research assistantships (RAs), and teaching assistantships (TAs). RAs require a measure of project work, and TAs require teaching each semester.

    For application information, see the LTI ``How to Apply'' page.


    The LTI Webmaster    		  



    LTI is part of the School of Computer Science at Carnegie Mellon University.
    This page is maintained by Stacey Young