Third-octave band spectra and spectrograms of DataSEC sounds

This dataset supports the spectral analysis presented in the associated study and is based on the DataSEC dataset (DOI: 10.5281/zenodo.15393250), a previously developed and validated collection by the authors. DataSEC contains 5,048 .wav audio recordings covering 22 environmental sound classes, further subdivided into a total of 40 sub-classes. For each recording, both the third-octave band spectrum and spectrogram are provided to support detailed spectral exploration. To offer practical spectral references for each sound class, third-octave band spectra and spectrograms were computed for all recordings. Each sub-class is treated as an independent category. Signal processing was performed using MATLAB R2024b Update 5, primarily leveraging functions from the Signal Processing Toolbox. The frequency range was set between 20 Hz and 20 kHz, consistent with standard practices in environmental acoustics and the typical range of human hearing. Given the variability in sound levels across the recordings, absolute sound pressure levels (SPL) were not used directly. Instead, each third-octave spectrum was min-max normalized, highlighting relative spectral patterns across different sound types and enabling meaningful comparisons. To capture temporal spectral variations, third-octave band spectrograms were computed using a 50 ms Hann window with 50% overlap. Each spectrogram displays time on the x-axis (in seconds), third-octave center frequencies on the left y-axis, and unweighted SPL on the color scale. This representation allows for the identification of both transient and continuous sound events and facilitates the interpretation of spectral dynamics across time and frequency. The dataset is organized into two main folders: "Third_octave_band_spectra.zip" contains one spectrum per audio file, grouped by sound class "Third_octave_band_spectrogram.zip" containing the corresponding spectrograms. All files are provided in .svg vector format to ensure maximum clarity and scalability. File names directly reference the corresponding .wav recordings in the original DataSEC dataset, ensuring seamless cross-referencing and traceability.