Package index • ohun

Prepare data for detection

Prepare annotations and acoustic data for automated detection

split_acoustic_data(): Splits sound files and associated annotations

get_envelopes(): Extract absolute amplitude envelopes

get_templates(): Find templates representative of the structural variation of sound events

summarize_reference(): Summarize temporal and frequency dimensions of annotations and gaps

summarize_acoustic_data(): Summarize information about file format in an acoustic data set

Automated detection

Functions implementing automated sound event detection

energy_detector(): Detects the start and end of sound events

optimize_energy_detector(): Optimize energy-based sound event detection

template_correlator(): Acoustic templates correlator using time-frequency cross-correlation

template_detector(): Acoustic template detection from time-frequency cross-correlations

optimize_template_detector(): Optimize acoustic template detection

Curating detection datasets

Exploration and manipulation of the output of detection functions

consensus_detection(): Remove ambiguous detections

merge_overlaps(): Merge overlapping selections

summarize_diagnostic(): Summarize detection diagnostics

label_detection(): Label detections from a sound event detection procedure

diagnose_detection(): Evaluate the performance of a sound event detection procedure

Built in datasets

Datasets included in baRulho

lbh1: Long-billed hermit recording

lbh2: Long-billed hermit recording

lbh_reference: Example data frame of a selection table including all sound events of interests

Additional functions

label_spectro(): Plot a labeled spectrogram

plot_detection(): Plot detection and reference annotations