A shazam like tool to store songs fingerprints and retrieve them

musig 🔈

GoDoc CircleCI

A shazam-like tool that allows you to compute song's fingerprints and reverse lookup song names.

It's more or less an implementation of the shazam paper as described in this awesome article

Installation

You will need to have go on your computer (version > 1.11 to be able to use go modules).

You will also need to have portaudio installed (brew install portaudio on macOS, apt install portaudio19-dev on Ubuntu / Debian, for other distributions you can search for the portaudio package), it is required for the listen command that listens on your microphone to match the recording against the database.

To build the binary:

git clone [email protected]:sfluor/musig.git
cd musig
make

You will then be able to run the binary with:

./bin/musig help

Usage

musig usage

To do some testing you can download wav songs by doing make download.

Load them with ./bin/musig load "./assets/dataset/wav/*.wav"

And try to find one of your song name with:

./bin/musig read "$(ls ./assets/dataset/wav/*.wav | head -n 1)"

You can also try to use it with your microphone using the listen command:

./bin/musig listen

If you want to record a sample and reuse it multiple times after you can also use the record command:

./bin/musig record

For more details on the usage see the help command:

A shazam like CLI tool

Usage:
  musig [command]

Available Commands:
  help        Help about any command
  listen      listen will record the microphone input and try to find a matching song from the database (Ctrl-C will stop the recording)
  load        Load loads all the audio files matching the provided glob into the database (TODO: only .wav are supported for now)
  read        Read reads the given audio file trying to find it's song name
  record      record will record the microphone input and save the signal to the given file
  spectrogram spectrogram generate a spectrogram image for the given audio file in png (TODO: only .wav are supported for now)

Flags:
      --database string   database file to use (default "/tmp/musig.bolt")
  -h, --help              help for musig

Use "musig [command] --help" for more information about a command.

Testing

To run the tests you can use make test in the root directory.

TODOs

  • improve the documentation
  • support for mp3 files
Owner
Sami Tabet
Software Engineer
Sami Tabet
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Comments
  • Segfault on 24bit files

    Segfault on 24bit files

    Greetings!

    It looks like parseRawData() segfaults on 24bit wav files, because there's no conversion function defined here

    	byteSizeToIntFunc = map[int]bytesToIntF{
    		16: bits16ToInt,
    		32: bits32ToInt,
    	}
    
    panic: runtime error: invalid memory address or nil pointer dereference
    [signal SIGSEGV: segmentation violation code=0x1 addr=0x0 pc=0x10a3643]
    
    goroutine 1 [running]:
    github.com/DylanMeeus/GoAudio/wave.parseRawData(0xc00010000c, 0x4, 0x102880, 0x10, 0x1, 0x2, 0xac44, 0x40998, 0x6, 0x18, ...)
    	...go/pkg/mod/github.com/!dylan!meeus/[email protected]/wave/reader.go:145 +0x143
    github.com/DylanMeeus/GoAudio/wave.ReadWaveFile(0x10d7ea8, 0x13, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, ...)
    

    I imagine the omission is due to there being no math constant defined for a max 24bit integer, which is understandable. It looks like other packages work around this by simply defining their own -- either by defining it as 8bitmax+16bitmax, or, in the case of mysql:

    const (
    	MaxUint24 = 1<<24 - 1
    	MaxInt24  = 1<<23 - 1
    	MinInt24  = -1 << 23
    )
    

    I'm happy to drop a PR if it'd be helpful, but I figured I'd just give you a heads up first, as I'm not 100% sure that my solution is correct

    Cheers,

  • Enhancement: compute the correlation between two matches instead of only counting the matches

    Enhancement: compute the correlation between two matches instead of only counting the matches

    This is to improve the matching process, it's very similar to what is described in the shazam paper, illustrations are from the shazam paper:

    A matching sample will look like: image

    Whereas a non-matching sample will look like: image

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