audio/SongRec: Simplify README.

Signed-off-by: Willy Sudiarto Raharjo <willysr@slackbuilds.org>
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@ -17,197 +17,3 @@ thinking that it is the concerned song.
A (command-line only) Python version, which I made before rewriting in
Rust for performance, is also available for demonstration purposes. It
supports file recognition only.
## How it works
For useful information about how audio fingerprinting works, you may
want to read [this article](http://coding-geek.com/how-shazam-works/).
To be put simply, Shazam generates a spectrogram (a time/frequency 2D
graph of the sound, with amplitude at intersections) of the sound, and
maps out the frequency peaks from it (which should match key points of
the harmonics of voice or of certains instruments).
Shazam also downsamples the sound at 16 KHz before processing, and cuts
the sound in four bands of 250-520 Hz, 520-1450 Hz, 1450-3500 Hz,
3500-5500 Hz (so that if a band is too much scrambled by noise,
recognition from other bands may apply). The frequency peaks are then
sent to the servers, which subsequently look up the strongest peaks in
a database, in order look for the simultaneous presence of neighboring
peaks both in the associated reference fingerprints and in the
fingerprint we sent.
Hence, the Shazam fingerprinting algorithm, as implemented by the
client, is fairly simple, as much of the processing is done
server-side. The general functionment of Shazam has been documented in
public [research
papers](https://www.ee.columbia.edu/~dpwe/papers/Wang03-shazam.pdf) and
patents.
Note: It is not mandatory, but if you want to be able to recognize more
formats than WAV, OGG, FLAC and MP3, you should ensure that you have
the `ffmpeg` package installed.
## Compilation
(**WARNING**: Remind to compile the code in "--release" mode for
correct performance.)
### Installing Rust
First, you need to [install the Rust compiler and package
manager](https://www.rust-lang.org/tools/install). It has been observed
to work with `rustc` 1.43.0 to the current rustc 1.47.0.
Install Rust and put it in path, for all distributions:
```bash
curl --proto '=https' --tlsv1.2 -sSf https://sh.rustup.rs | sh # Type
"1"
# Login and reconnect to add Rust to the $PATH, or run:
source $HOME/.cargo/env
# If you already installed Rust, then update it:
rustup update
```
### Install dependent libraries (nothing exotic)
Debian:
```bash
sudo apt install build-essential libasound2-dev libgtk-3-dev libssl-dev
```
Void Linux (libressl):
```shell
sudo xbps-install base-devel alsa-lib-devel gtk+3-devel libressl-devel
```
Void Linux (openssl):
```shell
sudo xbps-install base-devel alsa-lib-devel gtk+3-devel openssl-devel
```
### Compiling the project
This will compile and run the projet:
```bash
# For the stable release:
cargo install songrec
songrec
# For the Github tree:
git clone git@github.com:marin-m/songrec.git
cd songrec
cargo run --release
```
For the latter, you will then find the project's binary (that you will
be able to move or execute directly) at `target/release/songrec`.
## Sample usage
Passing no arguments or using the `gui` subcommand will launch the GUI,
and try to recognize audio real-time as soon as the application is
launched:
```
./songrec
./songrec gui
```
Using the `gui-norecording` subcommand will launch the GUI without
recognizing audio as soon as the software is started (you will need to
click the "Turn on microphone recognition" button to do so):
```
./songrec gui-norecording
```
The GUI allows you to recognize songs either from your microphone,
speakers (on compatible PulseAudio setups), or from an audio file. The
MP3, FLAC, WAV and OGG formats should be accepted for audio files if
FFMpeg is not installed, and any audio or video formats supported by
FFMpeg should be accepted if FFMpeg is installed.
The following commands allow to recognize sound from your microphone or
from a file using the command line (`listen` runs while the microphone
is usable while `recognize` recognizes only one song), use the `-h`
flag in order to see all the available options:
```
./songrec listen -h
./songrec recognize -h
```
By default, only the artist and track name of the concerned song are
displayed to the standard output, and other information may be
displayed to the error output. The `--csv` and `--json` options allow
to display more programmatically usable information to the standard
output.
The above decribes the newer CLI interface of SongRec, but an older
interface, operating only on audio files or raw audio fingerprints, is
also available and described below.
The following subcommand will try to recognize audio from the middle of
an audio file, and print the JSON response from Shazam servers:
```
./songrec audio-file-to-recognized-song sound_file.mp3
```
The following subcommands will do the same with an intermediary step,
manipulating data-URI audio fingerprints as used by Shazam internally:
```
./songrec audio-file-to-fingerprint sound_file.mp3
./songrec fingerprint-to-recognized-song
'data:audio/vnd.shazam.sig;base64,...'
```
The following will produce back hearable tones from a given
fingerprint, that should be able to fool Shazam into thinking that this
is the original song (either to the default audio output device, or to
a .WAV file):
```
./songrec fingerprint-to-lure 'data:audio/vnd.shazam.sig;base64,...'
./songrec fingerprint-to-lure 'data:audio/vnd.shazam.sig;base64,...'
/tmp/output.wav
```
When using the application, you may notice that certain information
will be saved to `~/.local/share/SongRec` (or an equivalent directory
depending on your operating system), including the CSV-format list of
the last recognized songs and the last selected microphone input device
(so that it is chosen back when restarting the app). You may want to
delete this directory in case of persistent issues.
## Privacy
SongRec collects no data and contacts no other servers than Shazam's.
SongRec does not upload raw audio data anywhere: only fingerprints of
the audio are uploaded, which means sequences of frequency peaks
encoded in the form of "(frequency, amplitude, time)" tuples.
This does not suffice to represent anything hearable alone (use the
"Play a Shazam lure" button to see how much this is different from full
sound); that means that no actually hearable sound (e.g voice
fragments) is sent to servers, only metadata derived on the
characteristics of the sound that may only suffice to recognize a song
already known by Shazam is being sent.
## Legal
This software is released under the [GNU GPL
v3](https://www.gnu.org/licenses/gpl-3.0.html) license. It was created
with the intent of providing interoperability between the remote Shazam
services and Linux-based deskop systems.
Please note that in certain countries located outside of the European
Union, especially the United States, software patents may apply.