Audio segmentation with in-built optimization: the tools for syllable segmentation are again very flexible.While the abundance of control parameters may initially seem daunting, for those who do wish to delve deeply this makes soundgen’s pitch tracker very versatile and offers a lot of power for high-precision analysis. Flexible pitch tracking: soundgen uses several popular methods of pitch detection in parallel, followed by their integration and postprocessing.So if you’d rather get started with model-building without delving too deeply into acoustics, you are one line of code away from your dataset. User-friendly approach: a single call to the analyzeFolder function will give you a dataframe containing dozens of commonly used acoustic descriptors for each file in an entire folder.Reasons to use soundgen for acoustic analysis might be: Soundgen builds upon the functionality of seewave, adding high-level functions for sound synthesis (see the vignette on sound synthesis) and acoustic analysis, particularly pitch tracking and audio segmentation. In R, the most extensive acoustic toolkit by far is the seewave package. For bird sounds, a sophisticated tool is Sound Analysis Pro. For in-depth analysis of individual mammalian sounds it’s hard to beat PRAAT (batch processing is possible, but a bit tricky, because PRAAT uses its own, rather unusual scripting language). There are numerous programs out there for performing acoustic analysis, including several open-source options and R packages.
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