Acoustilytix™: A Web-Based Automated Ultrasonic Vocalization Scoring Platform.
Title
Acoustilytix™: A Web-Based Automated Ultrasonic Vocalization Scoring Platform.
Creator
Ashley CB; Snyder RD; Shepherd JE; Cervantes C; Mittal N; Fleming S; Bailey J; Nievera MD; Souleimanova SI; Nyaoga B; Lichtenfeld L; Chen AR; Maddox WT; Duvauchelle CL
Publisher
Brain Sciences
Date
2021
2021-06-29
Description
Acoustilytix implements machine learning methodology in the USV detection and classification process and is recording-environment-agnostic. We summarize the user features identified as desirable by USV researchers and how these were implemented. These include the ability to easily upload USV files, output a list of detected USVs with associated parameters in csv format, and the ability to manually verify or modify an automatically detected call. With no user intervention or tuning, Acoustilytix achieves 93% sensitivity (a measure of how accurately Acoustilytix detects true calls) and 73% precision (a measure of how accurately Acoustilytix avoids false positives) in call detection across four unique recording environments and was superior to the popular DeepSqueak algorithm (sensitivity = 88%; precision = 41%).
Subject
Ultrasonic vocalizations (USVs) are known to reflect emotional processing, brain neurochemistry, and brain function. Collecting and processing USV data is manual, time-intensive, and costly, creating a significant bottleneck by limiting researchers’ ability to employ fully effective and nuanced experimental designs and serving as a barrier to entry for other researchers. In this report, we provide a snapshot of the current development and testing of Acoustilytix™, a web-based automated USV scoring tool.
Identifier
Rights
2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license
Format
Journal Article
URL Address
https://doi.org/10.3390/brainsci11070864
Issue
7
Volume
11
NEOMED College
NEOMED College of Medicine
NEOMED Department
Department of Pharmaceutical Sciences
Update Year & Number
Jan to Aug list 2021
Citation
Ashley CB; Snyder RD; Shepherd JE; Cervantes C; Mittal N; Fleming S; Bailey J; Nievera MD; Souleimanova SI; Nyaoga B; Lichtenfeld L; Chen AR; Maddox WT; Duvauchelle CL, “Acoustilytix™: A Web-Based Automated Ultrasonic Vocalization Scoring Platform.,” NEOMED Bibliography Database, accessed April 26, 2024, https://neomed.omeka.net/items/show/11785.