Spoken Language Processing

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Presentation transcript:

Spoken Language Processing Julia Hirschberg CS 4706 8/4/2019

Speech Processing How do you produce sounds that other people interpret as language? How does your hearer decode what you are trying to convey? In a conversation, how do you know when it’s your turn to talk? Once you decide what you want to say, how do you decide how to say it?: How do you decide where to pause in the sentence? How do you decide what words to emphasize? How do you decide what intonational contour to use? How do you convey your own feelings and emotions? 8/4/2019

Applications for Speech Technologies Speech synthesis (TTS): AT&T, IBM (Jeopardy 2/14-16), SitePal Speech recognition (ASR): Nuance Speech to Speech Translation Speech Search: Google Voice Search Homeland Security: Deception Detection, Dialect and Language ID, and Speaker ID, trust Spoken Dialogue Systems: Over-the-phone services: Voice Actions for Android Tutoring systems: KTH’s Ville Amtrak Julie (or here) Watson on Jeopardy feb 14-16 TTS: Charles St. West is the home of Mr. St. Clair. The city hall parking lot was chock full of cars. Jorge Posada catches for the Yankees. 8/4/2019

What will we do in this course? Learn about fundamental aspects of speech signals and how to analyze them Phonemes and phones: sounds of a language Acoustic/prosodic information: pitch, energy Intonational contours Study two basic speech technologies, TTS and ASR and their application to Spoken Dialogue Systems (SDS) Build your own SDS using the Festival and HTK Toolkits 8/4/2019

Speech tools and speech lab Course information Course syllabus and readings (Jurafsky & Martin, second edition; Keith Johnson, second edition) Speech tools and speech lab Courseworks: discussion, course files, gradebook TAs: Bob Coyne, Erica Cooper 8/4/2019

Projects and Exams Build and demo a Spoken Dialogue System Teams of 3 Organize your own or Advertise for team members on Courseworks discussion category “Find a team” or Send mail to coyne@cs.columbia.edu 4 Deadlines: Project Description TTS component (using Festival tools) ASR component (using HTK tools) SDS demos (during final exam period) Midterm (March 9) and final (May 2) in class 8/4/2019

Honor policy on syllabus Late policy on syllabus (5 ‘free’ late days per project for the semester) My office hours: M 4-6, CEPSR 705 Bob Coyne: TBD, CEPSR 7LW1 (Speech Lab) Erica Cooper: TBD, CEPSR 7LW1 (Speech Lab) 8/4/2019

Any Questions? 8/4/2019