Acoustic Analysis

Burst detection (burst.py)

This script does the following things:

1) Defines a function burst() which takes as input three arguments: a soundfile, start time, and end time.

2) Resamples sound file to 16,000 Hz.

In the soundfile waveform: 3) Within the window specified by the start and end times, goes through each sample one by one and determines whether it is a peak or valley.

4) Finds three biggest valleys in the waveform (corresponding to pressure peaks) within specified time window.

5) Gives each of these peaks a time-stamped score based on amount of change in waveform relative to neighboring samples

In the spectragram:

6) Now, takes a Mel frequency spectrum with freq above 300 Hz, in 5 ms windows.

7) Compares this window to the next 5 ms spectral window, and selects top three candidates with most change in the spectrum.

8) Compares waveform candidates to spectrum candidates, keeps those where time scores align

Calculates a burst score (burst strength) for remaining candidates. Using a linear model trained on the burst locations in TIMIT:

10) Selects candidate with highest burst score.

10) If there is no burst, returns a burst_time of -1.