Sex differences in the song circuit and song acoustic complexity in male and female house wrens

In this study, we compared neural song circuit morphology to singing behavior recorded in the field for 17 male and 18 female house wrens. The acoustic complexity of house wren songs was quantified using a recently published machine learning approach. This data set includes recordings of all house wren songs used in this analysis along with Raven selection tables defining the boundaries of each syllable. This includes 109 female songs. R code used to extract acoustic features and estimate element diversity and our proxy for song acoustic complexity are included. Summaries of acoustic variables for each song and each element are provided as well as files necessary to replicate the analysis. For each bird, we measured volume, cell number, cell density, and neuron soma size for three song circuits, Area X, HVC (used as a proper name), and the robust nucleus of the arcopallium (RA), and one control region, the nucleus rotundus (Rt). This data set includes these neural morphology measurement..., Wild house wrens were recorded in the field singing spontaneously or in response to playback recordings of male or female house wren songs. Songs were clipped from much longer song recordings with 1 second before the start and 1 second after the end of the song. No further processing occurred. All songs used in this analysis can be found in the \"songs.zip\" file. The start and end of each element in the song were defined manually in Raven using both the spectrogram and waveform. These boundaries can be found in the .txt file associated with each sound file (.wav file) in the \"songs.zip\" folder.
Signal-to-noise ratios (SNR) were used to select songs of suitable quality for the rest of the analysis. Users can use the \"snr.and.automatic.frequency.detection.r\" script to replicate this calculation for all sounds in the \"songs.zip\" file.  When songs with a suitable SNR were selected, we used this same R script to automatically detect the frequency boundaries of each element. These were then vi..., R can be used to run the code files (\"acoustic.space.and.ED.calculations\", \"snr.and.automatic.frequency.detection\", \"statistics.and.figs\"). These files can also be opened in Notepad.  Txt files associated with each sound file can be opened in Raven Pro or Raven Lite (free version) to visualize the boundaries of each element type. These files can also be opened in any program that can read .txt files.  , # Sex differences in the song circuit and song acoustic complexity in male and female house wrens

Wild house wrens were recorded in the field singing spontaneously or in response to playback recordings of male or female house wren songs. All songs used in this analysis can be found in the \"songs.zip\" file. The start and end of each element in the song were defined manually in Raven using both the spectrogram and waveform. These boundaries can be found in the .txt file associated with each sound file (.wav file) in the \"songs.zip\" folder.

Signal-to-noise ratios (SNR) were used to select songs of suitable quality for the rest of the analysis. Users can use the \"snr.and.automatic.frequency.detection.r\" script to replicate this calculation for all sounds in the \"songs.zip\" file. When songs with a suitable SNR were selected, we used this same R script automatically detect the frequency boundaries of each element. These were then viewed in Raven and corrected for any obvious deviation...