audio-processing

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audio-processing

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A handy nodejs package for audio processing. For example, it can extract frequencies from the audio and compute the pitch.

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# Audio-Processing

A handy nodejs package for audio processing.

For example, it can extract frequencies from the audio and compute the pitch.

The source code can be found on [https://github.com/fengzhang2011/audio-processing](https://github.com/fengzhang2011/audio-processing).

The npm package is on [https://www.npmjs.com/package/audio-processing](https://www.npmjs.com/package/audio-processing).

## 1. HOW TO USE

### 1.1 A simple test on the library

Just execute the following command.
```bash
$ cd build
$ cmake ..
$ make
$ ./audio_processing
```

### 1.2 Use it in the Javascript

This package has been published into the npm repository. Therefore, it can be installed via `npm`.
```bash
$ mkdir your_project
$ cd your_project
$ npm init
$ npm install audio-processing
```

NOTE:

If you encounter some issues like ```permission denied``` while installing it, especially in a docker container, try the following command.
Reason: The ```unsafe-perm``` boolean set to true to suppress the UID/GID switching when running package scripts.

```bash
# npm config set unsafe-perm true
```

Now you could use the code. The example code is as follows.

```javascript
const ap = require('audio-processing');

console.log(ap.hello());

async function test() {
let audio = await ap.readAudio("./wav/female.wav");
  console.log(audio.samplerate);
  ap.saveAudio("haha.wav", audio.wavdataL, audio.wavdataR, audio.samplerate, audio.bitdepth, audio.channels);
  console.log(ap.detectPitch(audio.wavdataL, audio.samplerate, 'acorr'));
  console.log(ap.detectPitch(audio.wavdataL, audio.samplerate, 'yin'));
  console.log(ap.detectPitch(audio.wavdataL, audio.samplerate, 'mpm'));
  // console.log(ap.detectPitch(audio.wavdataL, audio.samplerate, 'goertzel'));
  // console.log(ap.detectPitch(audio.wavdataL, audio.samplerate, 'dft'));

let ampfreq = await ap.ampfreq(audio.wavdataL, audio.samplerate);
  // console.log('ampfreq=', ampfreq);

let data = new Float32Array([0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19]);
  // console.log(data);

let freq_data = await ap.fft(data);
  // console.log(freq_data);

let td_data = await ap.ifft(freq_data.real, freq_data.imag);
  // console.log(td_data);
}

test();
```

## 2. CREDITS

This code uses the [FFTS](https://github.com/anthonix/ffts.git), [Pitch-Detection](https://github.com/sevagh/pitch-detection.git), [AudioFile](https://github.com/adamstark/AudioFile), [Opencore-AMR](https://sourceforge.net/projects/opencore-amr), [MiniMp3](https://github.com/lieff/minimp3), and [libsamplerate](https://github.com/erikd/libsamplerate).

Thanks for their great work.

The detailed versions in use are as follows:

| # | Project | Version | Date |
| ---| --- | --- | --- |
| 1 | FFTS | [fe86885](https://github.com/anthonix/ffts/tree/fe86885ecafd0d16eb122f3212403d1d5a86e24e) | Jun-17-2017 |
| 2 | Pitch-Detection | [7799a62](https://github.com/sevagh/pitch-detection/tree/7799a623c30ede739cb8d3c8fa3e0a9e5b200b58) | Oct-07-2018
| 3 | AudioFile | [a6430a0](https://github.com/adamstark/AudioFile/tree/a6430a05c859e43f3379e0fe078ae4e094d71602) | Jun-06-2017
| 4 | Opencore-AMR | [0.1.5](https://sourceforge.net/projects/opencore-amr/files/opencore-amr/opencore-amr-0.1.5.tar.gz/download) | Mar-16-2017
| 5 | MiniMp3 | [7295650](https://github.com/lieff/minimp3/commit/7295650ab38760846505897bd85b150022b9c570) | Sep-26-2018
| 6 | libsamplerate | [313685a](https://github.com/erikd/libsamplerate/commit/313685a7a94db5e8147c470ced811f03f3d2733c) | Mar-07-2019

## 3. THIRD-PARTY LIBRARIES

### 3.1 Supported Audio Format

#### 3.1.1 Format: .wav (WAV)

Copy the AudioFile source code

```bash
$ git clone https://github.com/adamstark/AudioFile
$ cd AudioFile
$ mkdir build
$ cd build
$ g++ -ansi -pedantic -Werror -O3 -std=c++17 -fPIC -fext-numeric-literals -ffast-math -c ../*.cpp
$ ar rcs libaudiofile.a *.o
```

Once these commands are done, the ```libaudiofile.a``` will be generated under the ```build``` folder.

Copy the header file ```src/AudioFile.h``` and ```libaudiofile.a``` to ```./include``` and ```./lib``` folders, respectively, into this repository.

#### 3.1.2 Format: .amr (AMR)

OpenAMR WB/NB

[https://sourceforge.net/projects/opencore-amr/files/opencore-amr/](https://sourceforge.net/projects/opencore-amr/files/opencore-amr/)

#### 3.1.3 Format: .mp3 (MP3)

MP3 decoder

[https://github.com/lieff/minimp3](https://github.com/lieff/minimp3)

### 3.2 Resample

#### 3.2.1 Sample Rate Converter

[libsamplerate](https://github.com/erikd/libsamplerate/commit/313685a7a94db5e8147c470ced811f03f3d2733c)

```bash
$ git clone https://github.com/anthonix/libsamplerate.git
$ cd libsamplerate
$ echo "set(CMAKE_C_FLAGS \"\${CMAKE_C_FLAGS} -fPIC\")" >> CMakeLists.txt
$ mkdir build
$ cd build
$ cmake ..
$ make
```

### 3.3 FFT and MFCC

#### 3.3.1 Compile the FFTS static library

```bash
$ git clone https://github.com/anthonix/ffts.git
$ cd ffts
$ echo "set(CMAKE_C_FLAGS \"\${CMAKE_C_FLAGS} -fPIC\")" >> CMakeLists.txt
$ mkdir build
$ cd build
$ cmake ..
$ make ffts_static
```

NOTE:
  We must enable the ```-fPIC``` flag when compiling the ffts static library, to enable the "Position Independent Code". Otherwise, it will generate the follow error:
```
/usr/bin/ld: ../lib/libffts.a(ffts.c.o): relocation R_X86_64_32S against `.text' can not be used when making a shared object; recompile with -fPIC
../lib/libffts.a: error adding symbols: Bad value
collect2: error: ld returned 1 exit status
make: *** [Release/obj.target/ssrc.node] Error 1
```

Once these commands are done, the ```libffts.a``` will be generated under the ```build``` folder.

Copy the header file ```include/ffts.h``` and ```libffts.a``` to ```./include``` and ```./lib``` folders, respectively, into this repository.

#### 3.3.2 MFCC compuation

The code are written based on these great documents. Thanks for the authors.

- [1] [Mel Frequency Cepstral Coefficient (MFCC) tutorial. James Lyons. ](http://practicalcryptography.com/miscellaneous/machine-learning/guide-mel-frequency-cepstral-coefficients-mfccs)
- [2] [Speech Processing for Machine Learning: Filter banks, Mel-Frequency Cepstral Coefficients (MFCCs) and What's In-Between. Haytham Fayek. ](https://haythamfayek.com/2016/04/21/speech-processing-for-machine-learning.html)
- [3] [Hamming Window, SPECTRAL AUDIO SIGNAL PROCESSING. Julius Orion Smith III. ](https://ccrma.stanford.edu/~jos/sasp/Hamming_Window.html)

### 3.4 Audio features

#### 3.4.1 Pitch

Compile the Pitch-Detection static library

```bash
$ git clone https://github.com/sevagh/pitch-detection.git
$ cd pitch-detection
$ mkdir build
$ cd build
$ g++ -I../include -ansi -pedantic -Werror -Wall -O3 -std=c++17 -fPIC -fext-numeric-literals -ffast-math -c ../src/*.cpp
$ ar rcs --plugin $(gcc --print-file-name=liblto_plugin.so) libpitch_detection.a *.o
```

Once these commands are done, the ```libpitch_detection.a``` will be generated under the ```build``` folder.

Copy the header file ```include/pitch_detection.h``` and ```libpitch_detection.a``` to ```./include``` and ```./lib``` folders, respectively, into this repository.

### 3.5 Noise reduction

#### 3.5.1 Weiner filter for Noise Reduction and speech enhancement.

Pascal Scalart. [Wiener Noise Suppressor based on Decision-Directed method with TSNR and HRNR algorithms.](https://www.mathworks.com/matlabcentral/fileexchange/24462-wiener-filter-for-noise-reduction-and-speech-enhancement)

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