Erosion as a novel Approach for removing Semantics and Comparison of different State-of-Art-Methods

Abstract

Through language, people convey not only pure semantics, but also information about themselves, such as age, gender, state of mind or health. The supralingual features that carry this information have been a subject of research for a long time. Various procedures have been proposed to remove unneeded semantics from speech recordings, in order to study supralingual information in natural speech. In this paper, we propose a new method for removing sematics, based on erosion, a morphological operator. We compare its effectiveness to different state-of-the-art methods. As established methods we consider two low pass filters with cut off frequencies of 450Hz and 1150Hz and Brownian noise. As a newer method we investigate a filter for spectro-temporal frequencies. To evaluate each method, appropriately processed recordings were presented to a group of participants in a perceptual experiment. The intelligibility was measured by means of the Levenshtein distance. Our results show that erosion itself performs similarly to the established methods, while a combination of erosion and low-pass filter outperforms all other methods.