Improving Frame Based Automatic Laughter Detection
نویسنده
چکیده
Laughter recognition is an underexplored area of research. My goal for this project was to improve upon my previous work to automatically detect laughter on a frame-byframe basis. My previous system (baseline system) detected laughter based on shortterm features including MFCCs, pitch, and energy. In this project, I have explored the utility of additional features (phone and prosodic) both by themselves and in combination with the baseline system. I improved the baseline system by 0.1% absolute and achieved an equal error rate (EER) of 7.9% for laughter detection on the ICSI Meetings database.
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