Semester.ly

Johns Hopkins University | EN.520.701

Current Topics in Language and Speech Processing

1.0

credits

Average Course Rating

(4.33)

This biweekly seminar will cover a broad range of current research topics in human language technology, including automatic speech recognition, natural language processing and machine translation. The Tuesday seminars will feature distinguished invited speakers, while the Friday seminars will be given by participating students. A minimum of 75% attendance and active participation will be required to earn a passing grade. Grading will be S/U.

Fall 2013

(4.5)

Fall 2014

(4.15)

Fall 2013

Professor: Sanjeev Khundanpur

(4.5)

Students found that the best aspect of this course was the hands-on lab experience, which allowed them to actual y perform some microsystem fabrication. They thought the lab procedures were never ful y explained and that the labs were often rushed because they were too long to complete during the al otted time. Students also thought the lectures were dry and did not effectively prepare students for the lab. Suggestions for improvement included additional support with the lab procedures, and more coordination between the professors. Prospective students should be prepared for a course that is time-consuming but has a moderate course load and some interesting lab activities.

Fall 2014

Professor: Sanjeev Khudanpur

(4.15)

Students praised this course for being a hands-on experience that al owed them to apply what they learned in the classroom in the lab. Perceived issues with the course varied; some students disliked how lectures were handled with one student believing that lectures often ran over their al otted times. Another student thought the lectures didn’t go into enough detail. Suggestions for improvement varied; however, multiple students wished that the course chal enged them to complete more up-to-date labs that dealt with more recent ideas and findings. Prospective students should know that students found the course to be an enjoyable, if time-consuming experience. 123