Vocalizations play a significant role in social communication across species. Analyses in rodents have used a limited number of spectro-temporal measures to compare ultrasonic vocalizations (USVs), which limits the ability to address repertoire complexity in the context of behavioral states. Using an automated and unsupervised signal processing approach, we report the development of MUPET (Mouse Ultrasonic Profile ExTraction) software, an open-access MATLAB tool that provides data-driven, high-throughput analyses of USVs. MUPET measures, learns, and compares syllable types and provides an automated time stamp of syllable events. Using USV data from a large mouse genetic reference panel and open-source datasets produced in different social contexts, MUPET analyzes the fine details of syllable production and repertoire use. MUPET thus serves as a new tool for USV repertoire analyses, with the capability to be adapted for use with other species.
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