Spectrographic song analysis

Knowledge graph centered on Spectrographic song analysis with 65 nodes and 133 connections. Top connected: Rocky Mountain Biological Laboratory, Gothic, Crested Butte, Pekania pennanti, Colorado East River Valley.

Method synopsis

Detailed measurement of acoustic parameters from spectrograms to quantify song characteristics and calculate vocal individuality metrics.

Synthesized from method descriptions across 3 papers using this protocol.

Procedure from a recent peer-reviewed implementation

Steps below were extracted from the most recent peer-reviewed implementation of this protocol in the corpus — Can rarefaction be used to estimate song repertoire size in birds? (2011), Current Zoology. Implementations in other papers (listed below) may differ.

1. Analyze recorded songs for syllable identification
   Create spectrograms using 256 point FFTs in a standardized window of 0-5.5 kHz and 0-8 seconds. Apply 100-contrast level and brightness level of 70. Create syllable identification key to aid in consistent syllable recognition across recordings. Identify and catalog each syllable in recordings longer than 1 minute containing at least 50 syllables.
   Quantities: 220 distinct syllables identified across all individuals, recordings >1 minute with ≥50 syllables used for analysisDuration: Not specifiedConditions: Excluded songs recorded during rainy or windy conditions
   Equipment: Raven Pro 1.3 software, Krein et al. 2009 reference
2. Create data sets for method comparison
   Generate three data sets of different sample sizes from individuals with sufficient recordings. Large data set: first 50 syllables from 16 individuals. Medium data set: first 100 syllables from 14 individuals. Small data set: first 150 syllables from 5 individuals. Each data set uses the same recordings to enable direct method comparison.
   Quantities: Large (L): 16 individuals × 50 syllables, Medium (M): 14 individuals × 100 syllables, Small (S): 5 individuals × 150 syllablesDuration: Not specifiedConditions: Used same recordings across all methods for accurate comparison
   Equipment: Previously recorded and analyzed songs

Typical Equipment

• Praat sound analysis software
• SPSS software

Output Measurements

• frequency measurements
• temporal measurements
• Beecher information statistics

Papers Using This Protocol (3)

Species Studied With This Protocol

Places Where Used