Signal Processing: Musical Instrument Recognition & Resources

In summary: Flutes and picolos are the most difficult instruments to play in the anharmonic range because they don't have a lot of resonators to capture energy. It's easier to play an instrument in the overtone range, where there are more resonators to capture energy.
  • #1
inadaze
20
0
Hi,
I was just wondering if anyone has any experience with signal processing. I am working with musical instrument recognition and would like some help. What is the main difference between musical instrument signals? Where can I get some resources on signal processing(I am using Matlab, but anything would be a great help).

Thanks
JAy
 
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  • #2
I do quite a lot of digital signal processing.

The reason different instruments sound different (even while playing the same note) is because each instrument produces its own blend of harmonics. The amount of power in the harmonics is a "fingerprint" of the instrument.

- Warren
 
  • #3
Wow, your helping me out everywhere on this forum. ha. thank you.
So, what your saying is that if I were to run an FFT on any sound and count the amount of Harmonics I would be able to tell what instrument it is?
What about a guitar for instance...depending on where the string is struck it seems that I get different sets of harmonics. Is that it, or do the same harmonics show up in the same position with only the peek height changing?

Thanks
Jay
 
  • #4
Theoretically, there's an infinite number of harmonics from every instrument. If you strike middle C (440 Hz), you'll get a harmonic at 880 Hz, 1320 Hz, etc.

The harmonics for middle C are always in the same place, regardless of the instrument. The relative heights of the peaks is what makes a trumpet sound like a trumpet and a piano sound like a piano. Some instruments have more second harmonic, while some have more third, etc.

You couldn't detect an infinite number of harmonics in practice, of course, because eventually the very weak high harmonics will not be discernable from random noise.

- Warren
 
  • #5
okay, that makes sense. Now when I analyze some instruments, I get peaks at dissonant intervals (not at steady intervals of the fundamental). What are these and how could I interpret them?

Jay
 
  • #6
Most musical instruments resemble one of two wave problems - a string bound at both ends, or a tube open at one or both ends. However, they are not perfect. There are resonators built in, and the mouth acts as a resonator as well. If a resonator can capture one frequency, imperfections might translate that energy to another frequency.

Horns, for instance, might capture some energy from longitudinal sine waves and convert them to bessel functions at their flared ends.

I bet flutes and picolos are not producing much in the way of these anharmonic signals.

Njorl
 

1. What is signal processing?

Signal processing is the manipulation and analysis of signals that contain information. It involves various techniques for extracting, filtering, and interpreting information from signals, such as audio, images, and video.

2. How does signal processing relate to musical instrument recognition?

Signal processing plays a crucial role in musical instrument recognition by analyzing the unique signal patterns produced by each instrument. These patterns are then used to train algorithms that can identify different instruments and their characteristics, such as pitch and timbre.

3. What are some challenges in implementing musical instrument recognition using signal processing?

One of the main challenges is dealing with the variability and complexity of real-world musical signals. Instruments can produce a wide range of sounds, and the same instrument can sound different depending on factors such as playing style and environment. Additionally, background noise and overlapping sounds from multiple instruments can make it difficult to accurately identify a single instrument.

4. What are some resources for learning about signal processing and musical instrument recognition?

There are many online resources available for learning about signal processing and musical instrument recognition, including courses, tutorials, and research papers. Some popular sources include the IEEE Signal Processing Society, Coursera, and the International Society for Music Information Retrieval (ISMIR).

5. How is signal processing used in the music industry?

Signal processing is used in the music industry in various ways, such as audio compression and enhancement, noise reduction, and audio effects. It is also used in the development of musical instruments, software, and technologies for recording, mixing, and producing music.

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