There are some piano tuners I've found who are a bit on the spectrum, who believe they can tune a piano in a way that no digital device can replicate. I'm skeptical, and would like to see how this method holds up against one of these savants.
Spectral analysis has indeed been around as a concept for centuries and there have been apps based on the FFT for decades, so definitely nothing new there.
What I have implemented however, while based in known concepts and techniques, allows to achieve real-time, low latency and high resolution (both in time and frequency dimensions) performance that I believe are out of reach of established (published) methods.
The apps you link are most likely making use of the FFT, which has become widely supported with efficient hardware acceleration and easy to use libraries, because of its central role in ubiquitous DSP applications, e.g. compression.
I would be interested in any publications or at least technical descriptions of algorithms/systems that achieve similar performance!
It is more complex than the one described here. The idea is the same but for a working solution many different coefficients are needed and adjusted properly. Resonances are adjusted to have some match to the human perception.
It is all time domain as there are no real frequencies in sound.
It is good to see the idea investigated by more people but the man should not try to claim it as his own. We are doing such tings for years and I want this knowledge stays to people so no one should claim it
Sounds really interesting! Could you share some description of the algorithm used for chord detection? What model of tonality are you using for pitch/chord naming?
There are some piano tuners I've found who are a bit on the spectrum, who believe they can tune a piano in a way that no digital device can replicate. I'm skeptical, and would like to see how this method holds up against one of these savants.
And this is a tuner using same algorithm: https://apps.apple.com/us/app/resonance-chromatic-tuner/id16...
Also very old stuff :)
I have such app for more than 4 years. Your algorithm is not new - it is new for you only :) Here is the app: https://play.google.com/store/apps/details?id=com.bialamusic...
https://apps.apple.com/us/app/chord-detector/id1495811175
Spectral analysis has indeed been around as a concept for centuries and there have been apps based on the FFT for decades, so definitely nothing new there. What I have implemented however, while based in known concepts and techniques, allows to achieve real-time, low latency and high resolution (both in time and frequency dimensions) performance that I believe are out of reach of established (published) methods. The apps you link are most likely making use of the FFT, which has become widely supported with efficient hardware acceleration and easy to use libraries, because of its central role in ubiquitous DSP applications, e.g. compression. I would be interested in any publications or at least technical descriptions of algorithms/systems that achieve similar performance!
Is it the same algorithm or a similar domain? Overlap can exist
It is more complex than the one described here. The idea is the same but for a working solution many different coefficients are needed and adjusted properly. Resonances are adjusted to have some match to the human perception. It is all time domain as there are no real frequencies in sound.
It is good to see the idea investigated by more people but the man should not try to claim it as his own. We are doing such tings for years and I want this knowledge stays to people so no one should claim it
Sounds really interesting! Could you share some description of the algorithm used for chord detection? What model of tonality are you using for pitch/chord naming?
My email is alex@mlazev.com I will write some details when I have time.