Acoustic Analysis

Burst detection (burst.py)

This script defines a function burst()

-- input 1) the name of a soundfile, 2) start time (in seconds), and (3) end time of an analysis window where we will look for a burst.

-- output 1) a burst_time (in seconds), and 2) a burst_score which is a measure of how much like a burst the burst is.

The script does the following things:

1) Resamples sound file to 16,000 Hz.

With the Audio Waveform:

2) within the window specified by the start and end times, goes through each sample and determines whether it is a peak or valley.

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

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

Compute a series of Mel Frequency Spectra:

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

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

7) 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:

8) Selects candidate with highest burst score.

9) If no burst is detected, returns a burst score of 0 and a burst_time of -1.