Correlation of speech/non-speech events with photo-plethysmographic (PPG) signal
Correlation of speech/non-speech events with photo-plethysmographic (PPG) signal
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The use of photoplethysmogram signal (PPG) for heart monitoring is commonly found nowadays in smartphones and wrist wearables. Besides heart rate or sleep monitoring common usage, it has been proved that information from PPG can be extracted for other uses, like person verification, for example. In this work, we evaluate whether if speech/non-speech events can be inferred from fluctuations they might cause in the pulse signal. In order to do so, an exploration on end-to-end convolutional neural network architectures is done for performing both feature extraction and classification of the mentioned events. The results are motivating, detecting speech in PPG signal with a 68.2% AUC using the best performing architecture. On the other hand, a first experiment on speaker’s voice pitch detection is done, in order to check if a prosody marker such as pitch variation could be present in PPGs, but such clue is not clearly found in the results obtained. Nevertheless, the correlation between speech and PPG signal is proven and the way is paved for further experiments on this topic.Descripció
Treball fi de màster de: Master in Intelligent Interactive Systems
Tutors: Jordi Luque, Mireia Farrús