CS 6998 Computational Approach to Emotional Speech Instructor: Prof. Julia Hirschberg Columbia University 12/21/2009 Julia’s Little Helper: A Real-time Demo of Cantonese/Mandarin Emotional Speech Detection William Y. Wang Computer Science Suzanne Yuen Mechanical Engineering
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CS 6998 Computational Approach to Emotional Speech Instructor: Prof. Julia Hirschberg
Julia’s Little Helper : A Real-time Demo of Cantonese/Mandarin Emotional Speech Detection. Suzanne Yuen Mechanical Engineering. William Y. Wang Computer Science. CS 6998 Computational Approach to Emotional Speech Instructor: Prof. Julia Hirschberg Columbia University 12/21/2009. - PowerPoint PPT Presentation
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CS 6998 Computational Approach to Emotional Speech
Instructor: Prof. Julia HirschbergColumbia University 12/21/2009
3. Lexical Features: ASR using a HMM acoustic model trained on
Mandarin Broadcast News [1] and a simple hand-written decoding
dictionary.
4. Prosodic Features: Energy and Tonal Features
5. Real-time drawing of pitch contour, waveform and energy.
6. A text-to-speech agent to greet and teach user how to use this
demo.
[1] Yang Shao, Lan Wang, E-Seminar: an Audio-guide e-Learning System, IEEE International Workshop
on Education Technology and Training (ETT) 2008.
Lexical Scoring 1-3pts Energy 1 pt Tone 1 pt
Dictionary of Affects in Language
by Dr. Cynthia Whissell
Words Pleasantness
Activeness
Imagery
affect 1.7500 1.8571 1.6
affection
2.7778 2.2500 2.0
success 2.8571 1.8000 1.4
successes
3.0000 2.0000 1.4Total words: 8742 words were included. Source: It was actually developed using various sources, for example, college student essays, interviews and teenagers description of their own emotion state. So, it can have a broad coverage and avoid biased data.