| Summary: | VoxLog is a portable voice accumulator, that uses both an accelerometer that measures skin vibrations and a regular microphone to collect data. The goal of the thesis was to implement and evaluate methods that based on this data estimate the three different voice parameters fundamental frequency, phonation and soundpressure level. For pitch, three different methods were evaluated. The different methods all require relatively low computational power since the goal was to implement at least one of them on the digital signal processor in the VoxLog. The results from these evaluations show that the best estimations of pitch were made with a FFT-based approach that uses phase information to get an estimation with high frequencyresolution. Phonation is estimated with an energy based voice activity detection method.This estimation is then used to choose when sound pressure level should be estimated. Here one of the main problems was to make a distinction between when sound pressure level should be estimated for the wearer of the VoxLog or when an estimation should be made for the background noise. This was solved by implementing a time window before and after phonation were neither is estimated. For both pitch and sound pressure level a feedback functionality was implemented. The feedback is given to the user via vibrations in the VoxLog, the feedback is given when estimated parameters break set limits on pitch or sound pressure level.
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