Yell_ID: Yellowhammer individual identity across transmission distances

General Description Yell_ID is an open-access dataset of Yellowhammer (Emberiza citrinella) song recordings collected during controlled transmission experiments using Audiomoths. The dataset was designed to investigate how individual vocal signatures degrade over 7 distances (from 6.5 m to 200 m). It provides a valuable resource for studying individuality in bioacoustics, and for training individual recognition algorithms under low signal-to-noise ratio (SNR) conditions. The dataset consists of training and testing sets. In addition to the training dataset. A data augmentation script is provided to increase the variability of the audio samples for more robust training. A catalog of the repertoire for the 10 individual yellowhammers used in the transmission test is also included, detailing the song types for each individual. The archive BirdNET_model.zip contains the best-performing custom BirdNET model developed for individual Yellowhammer identification in the accompanying study. The model performs closed-set classification of the ten individuals represented in Yell_ID. The folder Transmission_Test_Data contains the CSV file with metadata that was used to support the work reported in the pre-print: https://doi.org/10.64898/2025.12.19.695494 For more information, please see the README.txt file as well as the accompanying work. Once unzipped, the 'Yell_ID_Set' folder should be approximately 500 MB.