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Course Overview

Course Overview. Lecture 1 Spoken Language Processing Prof. Andrew Rosenberg. Spoken Language Processing. How do computers interact with speech? C omputational approaches help us understand language and spoken communication. Speech Recognition. Voice Dialing Voice mail transcription

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Course Overview

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  1. Course Overview Lecture 1 Spoken Language Processing Prof. Andrew Rosenberg

  2. Spoken Language Processing • How do computers interact with speech? • Computational approaches help us understand language and spoken communication. Symbolic and Direct Modeling of Prosody

  3. Speech Recognition • Voice Dialing • Voice mail transcription • Closed Captioning • Interactive Voice Response / Spoken Dialog Systems • Keyword Spotting • Continuous Speech Recognition • Domain Specific vs. Open Domain Symbolic and Direct Modeling of Prosody

  4. Speech Synthesis • Navigation Systems • Garmin • Google Maps • IBM Watson • Bank by phone • Spoken Dialog Systems • Screen Readers Symbolic and Direct Modeling of Prosody

  5. How much information is in speech? • Words (Lexical Content) • Syntax • Semantics • Pragmatics • Speaker Identity • Gender, Personality • Speaker State • Discourse Acts Symbolic and Direct Modeling of Prosody

  6. Other applications • Video retrieval • “Rich Transcription” • Speech Segmentation • Emotion Analysis • Speech-to-speech translation • Intelligence Applications • Deception • Trust • Language & dialect Identification Symbolic and Direct Modeling of Prosody

  7. Broader Scientific Questions • How do you produce sounds that other perceive as language? • How does a hearer decode what you are trying to express? • How and why do you use prosodic variation? • Phrasing • Emphasis • Intonational Contours • Emotion, sarcasm, etc. • How does smooth turn taking happen? Symbolic and Direct Modeling of Prosody

  8. What will be covered in this course. • Project driven course. • Spoken Dialog System • Recognize Speech • CMU Sphinx • Make a decision • Generate Speech • Festival Symbolic and Direct Modeling of Prosody

  9. How the course is structured • Speech Recognition • Speech Synthesis • Analysis of additional information from speech • Speaker ID • Prosody/Intonation • etc. Symbolic and Direct Modeling of Prosody

  10. Project and Exams • Build a Spoken Dialog System • 4 Deadlines • Project Description (and team membership) • Speech Recognition Component • Speech Synthesis Component • Full system with demo. (Start on this early) • Project writeup. • In class midterm. Symbolic and Direct Modeling of Prosody

  11. The syllabus and course policies • course webpage: • http://eniac.cs.qc.cuny.edu/andrew/slp/syllabus.html Symbolic and Direct Modeling of Prosody

  12. Questions? • Policies • Course mechanics • Expectations Symbolic and Direct Modeling of Prosody

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