<< Chapter < Page Chapter >> Page >
Background on analyzing signals in the time-frequency representation.

The most natural way of analyzing the notes of an audio signal is through a time-frequency representation of it. This time-frequency representation is known as a spectrogram. However, this spectrogram has some resolution issues stemming from the windowing operation used on the signal in order to compute the STFT (Short-Time Fourier Transform) of it, putting it in the form we see: time vs. frequency. This windowing has an effect not unlike the Heisenberg Uncertainty Principle. A wide window improves the frequency resolution, and a narrow window improves the time resolution, thus we can never achieve a higher resolution in both the frequency and time domain (shown in figure below). However, we need to achieve a high resolution in both to analyze the notes with great precision. Time-Frequency Blurring

Get Jobilize Job Search Mobile App in your pocket Now!

Get it on Google Play Download on the App Store Now




Source:  OpenStax, Music transcription through frequency reassignment. OpenStax CNX. Dec 19, 2011 Download for free at http://cnx.org/content/col11393/1.1
Google Play and the Google Play logo are trademarks of Google Inc.

Notification Switch

Would you like to follow the 'Music transcription through frequency reassignment' conversation and receive update notifications?

Ask