Using speech technology to enhance isotope ID and classification

Scientific advances are often made when researchers identify mathematical or physical commonalities between different fields and are able to apply mature techniques or algorithms developed in one field to another field which shares some of the same challenges. The authors of this paper have identified similarities between the unsolved problems faced in gamma-spectroscopy for automated radioisotope identification and the challenges of the much larger body of research in speech processing. In this paper we describe such commonalities and use them as a motivation for a preliminary investigation of the applicability of speech processing methods to gamma-ray spectra. This approach enables the development of proof-of-concept isotope classifiers, whose performance is presented for both simulated and field-collected gamma-ray spectra.