Extended high frequencies for fricative classification in conversational speech

Abstract

The current study examines whether the information contained in Extended High Frequencies (EHFs) can improve random forest classification accuracy for fricatives in conversational speech. Prior phonetic research has investigated fricative categorization based on their acoustic characteristics, including spectral, temporal and amplitudinal measures. The spectral measures in these studies have largely been limited to frequency information below 8 kHZ. Only a few studies have examined the contribution of EHFs, energy exceeding 8 kHz. These studies have primarily focused on laboratory speech, so little is currently known about the role of EHFs in more spontaneous, conversational speech styles. Using a corpus of sociolinguistic interview speech from Western Canadian English sampled at 44.1kHz, we compare classification models with and without frequencies above 8 kHz. We discuss the influence of EHFs on the categorization of fricative identity, and share a cost-benefit analysis of sampling at higher frequencies for speech research corpora.