Telestra App Note

Automated Spectral Analysis Plots in Telestra (#108)

Did you know that you can automatically generate spectral analysis plots for sound model tuning and Level D/Type 7 FFS certification? All you need is a way to visit the proper web address for the desired Waveset on the Telestra system.

The plots we're going to generate will compare audio data recorded inside the simulator against audio data contained in reference files that were previously deemed acceptable for your particular type of aircraft (and your desired fidelity level). On the Telestra system, recorded files have a .tsr file extension (e.g., library000_group65535_index001.tsr), and the reference files are traditionally in .wav format. Both sets of files should reside in the appropriate locations on the Telestra system before proceeding.

Please take note of the "index001" part of the record file's name. During automated plot generation, the Telestra system will attempt to pair this record file with a reference .wav file name ending in the same number (when converted to an integer). For example, a reference .wav file named "test_case_001.wav" will match our sample record file, as will a .wav file named "testcase1.wav".

Now down to business. The web address to visit is:

 http://[server]/auralcue/sa/auto_gen?waveset=[waveset]

... or...

 http://[server]/auralcue/sa/auto_gen?waveset=[waveset]&subdir=[subdir]

... depending on the organizational structure of sound files on the Telestra system. Of course, you replace "[server]" and "[waveset]" as appropriate for your application.

The Telestra will then proceed with spectral analysis, and answer your request with a PDF file containing the charted values.

Sweet!

A couple of notes about this process:

  1. When you perform the analysis through Telestra's RMS web interface, you get to select which pairs of files to analyze. When running the plots automatically, however, you do not get to specify which matches to include; the system will include all matching pairs of files, including the background noise profile (index000), if applicable.
  2. You should be able to write a script using any of the powerful command line utilities available for your system (like "curl" on Mac or "wget" on Linux or Windows), or by using the appropriate libraries in your favorite scripting language. ASTi recommends using Python.