Ways to identify (musical) scores [closed]_问答_开发者

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I'm searching ways to identify scores, when someone is playing i.e. guitar. How can I manage that? I've heard that midi stores music data as musical scores. I wonder if it's a good solution.

MIDI does store musical scores, but it doesn't (normally) extract them from recorded sounds. You can't take an mp3 file and "convert it to MIDI", in a standard or entirely reliable way.

You create a MIDI file using a recorder (or "sequencer"), which might be a desktop application where you "write the score" like a composer does, or it might be a musical device like a keyboard, which records which keys you press, how hard and for how long, and interprets that as a score.

A MIDI player takes the data/score, and reproduces it using its own voice (or "sound font" if you like). So the advantage of MIDI data is firstly that the voice is already available on the playback device (and so the data is very compact), and second that the same data ("tune") can be played using different voices ("instruments")[*].

I believe there are MIDI guitars, but I don't know how "good" they are. The tone of an electric guitar comes in part from resonances of the solid body. This could of course be imitated by the voice at playback time, but there are bound to be some things that you can do with an electric guitar but which the MIDI format cannot capture or represent (for example I'd guess feedback is impossible).

Software exists to extract MIDI data from recorded sound - this is a bit like the way OCR extracts ASCII character data from images of text. It's not a major means of recording someone's guitar-playing, but if what you want is to get a first approximation to the score/tabs, you could try it.

Here's a randomly-selected example, found by Googling "convert from wav to MIDI":

http://www.pluto.dti.ne.jp/~araki/amazingmidi/

[*] But members of the audience, you find yourselves wondering, "what is this mindless automaton which bangs out the tunes it's instructed to, without comprehension or any aesthetic sense". Ladies and gentlemen, Colin Sell at the piano.

Music recognition/retrieval is an extremely difficult and almost entirely unsolved AI problem. Try to extract the frequency from a signal file of someone playing a single unwavering note one time - it's much more difficult than just "apply Fourier transform, read off solution". Compound that with polyphony, noise, rubato, vibrato/portamento, plus the fact that (contrary to speech recognition) we don't even have a working a-priori model of what music actually is, and you begin to see the difficulty. There are absolutely fascinating research papers and even entire conferences on the topic, but in the short term, you're just plain out of luck.

Are you aware you are attempting something extremely difficult? It's a very complex topic you could spend years researching yourself or pay $$$$$$ for existing commercial solutions.

MIDI is a reasonable choice for your output format.

For the rest you will need Fast Fourier Transforms working off a high-resolution capture of the input analogue sounds plus at least seven years of musical theory.

Good luck.

If the player is playing in tune, there will be very distinct frequencies in the signal, or at least frequencies with a mathematical separation. It may be possible to characterise a signal using spectral analysis to distinguish music from noise; or at least melodic music from noise - avant guarde experimental music may not pass ;). The distinction may become more difficult with multiple instrumentalists, percussion, and non-standard or poor tuning; traditional Chinese or Indian music for example uses different scales than western music.

Extracting the frequencies in the signal will require signal processing techniques such as Fast Fourier Transform. Categorising the signal as music/not music could be done by statistical analysis, or AI techniques such as neural networks or fuzzy logic