This week was mainly focused on planning how to move forward with our project, what to keep and what to change. More details about this can be found below in my statement of work, but the main part is that I will have a new task in the project, speech tone analysis. I gathered up the datasets and researched previous projects that used this (unfortunately there aren’t many), downloaded software (Praat) to analyze voice waveforms. Some problems I may face are that 1. there is not much research on the subject and 2. it is pretty late in the semester, so I am going to have to make progress really quickly.
Copy of my Statement of Work here:
As Patrick described above, there are a few changes to our project. I will still work on the web application, but since we will not be able to make the physical product, our original plan of connecting the Web application with the Raspberry Pi will no longer be possible.
The original web application was going to communicate with the RPi and receive textual journal entries of the user. Since we will no longer be making the physical product, the tasks related to setting up communication between the Raspberry Pi and web application had to be replaced.
Therefore I will work on speech tone analysis to complement Patrick’s work on facial emotion analysis and Vinay’s sentiment/text analysis. Speech tone analysis uses the voice waveforms to train and classify emotions. Waveforms contain information like pitch and formants that can be used as features. The classifier used to train will be an SVM because the size of our dataset is relatively small and there are not many features that need to be extracted.
I will be using Praat (http://www.fon.hum.uva.nl/praat/) voice analysis software to extract voice waves and measure values such as pitch and formants from sound recordings. The datasets I will use is the Ryerson Audio-Visual Database of Emotional Speech and Song (RAVDESS) which can be found here: https://www.kaggle.com/uwrfkaggler/ravdess-emotional-speech-audio?fbclid=IwAR2qFqomaS_N32Oke3Lhbil-wKsI35LZFrY55tMveIkT1ib2nCZxgCiywdo and the Toronto emotional speech set (found here: https://tspace.library.utoronto.ca/handle/1807/24487).
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