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.

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 June 21, 2024, https://neomed.omeka.net/items/show/11785.