Showcase 2018

To explore the impact and applications of sentiment analysis algorithms on human emotions, the Speech2Mood system extracts sentiment from spoken language and displays the analysed mood visually. A Raspberry Pi microcomputer running a Python script is used to process speech input and to change colour and mood-orientation of the full-spectrum lighting inside the customer feedback display box. This display type used was chosen to promote interaction with the project. As attendees leave the exhibition space, they are prompted to leave their spoken feedback in the microphone catchment area. Real-time code processes are shown on an adjacent screen.

Speech2MoodTad

BSc [Hons] C

reative Media Technologies

McAllister

After testing and tuning the sentiment extraction code stack, keyword detection accuracy with spoken input in a moderately busy room was good. Using the Google Natural Language Processing APIs, sentiment detection with clearly spoken speech was reliable. I am confident that further environmental tuning and microphone optimisation improve the quality of the results.