~ Analytical Approaches To World Music - Microtonal Scale Exploration in Central Africa

At the 2012 AAWM conference we presented a way to explore tone scales in the music of Central Africa. Since the audience consisted of (ethno)musicologists, the main focus of the presentation was on the applicication part, the technical aspects were only briefly mentioned.

The extended abstract can be consulted: Towards the tangible: microtonal scale exploration in Central-African music

The conference program itself was very diverse and interesting.

Tarsos, Computational ethnomusicology, Presentation, featured, HoGent, and Computational musicology

2012.05.11-Towards_the_Tangible_-_Microtonal_Scale_Exploration_in_Central-African_Music.odp and AAWM_abstract_short.doc

~ TarsosDSP Release 1.2

Today a new version of the TarsosDSP library was released. TarsosDSP is a small library to do audio processing in Java. It features two new pitch detectors. An AMDF pitch detector, contributed by Eder Souza of Brazil and a faster implementation of YIN kindly provided by Matthias Mauch of Queen Mary University, London.

Find your oven fresh baked binaries at the TarsosDSP Release Repository.

TarsosDSP and HoGent

PitchDetector.png

~ Guest Lecture at MIT - Ethnic Music Analysis: Challenges & Opportunities - Tarsos as a Case Study

Thursday the 3th of May I gave a guest lecture titled ‘Ethnic Music Analysis: Challenges & Opportunities’ it featured Tarsos as a Case Study. The goal was to identify the difficulties when dealing with ethnic music and to show a possible approach, the approach implemented by Tarsos.

The invitation to give the guest lecture came from Michael Cuthbert who is one of the driving forces behind music21. The audience was a small group of double majors in both musicology and computer science: the ideal profile to gather useful feedback.

Computational ethnomusicology, HoGent, and Presentation

2012.05.03-Ethnic_Music_Analysis.pdf and 2012.05.03-Ethnic_Music_Analysis.odp

~ TarsosDSP Release 1.0

After about a year of development and several revisions TarsosDSP has enough features and is stable enough to slap the 1.0 tag onto it. A ‘read me’, manual, API documentation, source and binaries can be found on the TarsosDSP release directory. The source is present in the
What follows below is the information that can be found in the read me file:

TarsosDSP is a collection of classes to do simple audio processing. It features an implementation of a percussion onset detector and two pitch detection algorithms: Yin and the Mcleod Pitch method. Also included is a Goertzel DTMF decoding algorithm and a time stretch algorithm (WSOLA).

Its aim is to provide a simple interface to some audio (signal) processing algorithms implemented in pure JAVA. Some TarsosDSP example applications are available.

The following example filters a band of frequencies of an input file testFile. It keeps the frequencies form startFrequency to stopFrequency.

AudioInputStream inputStream = AudioSystem.getAudioInputStream(testFile);
AudioDispatcher dispatcher = new AudioDispatcher(inputStream,stepSize,overlap);
dispatcher.addAudioProcessor(new HighPass(startFrequency, sampleRate, overlap));
dispatcher.addAudioProcessor(new LowPassFS(stopFrequency, sampleRate, overlap));
dispatcher.addAudioProcessor(new FloatConverter(format));
dispatcher.addAudioProcessor(new WaveformWriter(format,stepSize, overlap, "filtered.wav"));
dispatcher.run();

Quickly Getting Started with TarsosDSP

Head over to the TarsosDSP release repository and download the latest TarsosDSP library. To get up to speed quickly, check the TarsosDSP Example applications for inspiration and consult the API documentation. If you, for some reason, want to build from source, you need Apache Ant and git installed on your system. The following commands fetch the source and build the library and example jars:

git clone https://JorenSix@github.com/JorenSix/TarsosDSP.git
cd TarsosDSP/build
ant tarsos_dsp_library #Builds the core TarsosDSP library
ant build_examples #Builds all the TarsosDSP examples
ant javadoc #Creates the documentation in TarsosDSP/doc

Source Code Organization and Examples of TarsosDSP

The source tree is divided in three directories:

• src contains the source files of the core DSP libraries.
• test contains unit tests for some of the DSP functionality.
• build contains ANT build files. Either to build Java documentation or runnable JAR-files for the example applications.
• examples contains a couple of example applications with a Java Swing user interface:
  
  
  
  • SoundDetector show how you loudness calculations can be done. When input sound is over a defined limit an event is fired.
  • PitchDetector this demo application shows real-time pitch detection. When pitch is detected the hertz value is printed together with a probability.
  • PercussionDetector show the percussion (onset) dectection. Clapping your hands causes an event. This demo application also shows the influence of the two parameters on the algorithm.
  • UtterAsterisk a game with the goal to sing as close to a melody a possible. Technically it shows real-time pitch detection with YIN or MPM.
  • Spectrogram in Java shows a spectrogram and detected pitch, either live or from an audio file. It is interesting to see which frequencies are picked as fundamentals.
  • Goertzel DTMF decoding an implementation of the Goertzel Algorithm. A fancy user interface shows what goes on under the hood.
  • Audio Time Stretching – Implementation in Pure Java Using WSOLA an implementation of a time stretching algorithm. WSOLA makes it possible to change the play back speed of audio without changing the pitch. The play back speed can be changed at any moment, even when there is audio playing.

featured, WSOLA, TarsosDSP, HoGent, Music Information Retrieval, Java, Code, and Command Line Application

~ Oscilloscope in TarsosDSP

The DSP library for Taros, aptly named TarsosDSP, now includes an implementation of an oscilloscope.

The source code of the Java implementation can be found on the TarsosDSP github page. That is all.

HoGent and TarsosDSP

~ Dan Ellis' Robust Landmark-Based Audio Fingerprinting - With Octave

This blog post documents how to get the Matlab implementation by Dan Ellis of Avery Wangs Industrial-Strength Audio Search Algorithm running with GNU Octave on Ubuntu (and similar Linux distributions).

The Dan Ellis implementation is nicely documented here: Robust Landmark-Based Audio Fingerprinting . To download, get info about and decode mp3’s some external binaries are needed:

  













  
#install octave if needed
sudo apt-get install octave3.2
#Install the required dependencies for the script
sudo apt-get install mp3info curl

#mpg123 is not present as a package, install from source:
wget http://www.mpg123.de/download/mpg123-1.13.5.tar.bz2
tar xvvf mpg123-1.13.5.tar.bz2
cd mpg123-1.13.5/
./configure
make
sudo make install

In mp3read.m the following code was changed (line 111 and 112):

  



  
mpg123 = 'mpg123'; % was fullfile(path,['mpg123.',ext]);
mp3info = 'mp3info'; % was fullfile(path,['mp3info.',ext]);

Then, the demo program runs flawlessly when executing octave -q demo_fingerprint.m.

Running the demo with the original code with GNU Octave, version 3.2.3 takes 152 seconds on a PC with a Q9650 @ 3GHz processor. A small tweak can make it run almost 8 times faster. When working with larger data sets (10k audio files) this makes a big difference. I do not know why but storing a hash in the large hash table was really slow (0.5s per hash, with 900 hashes per song…). Caching the hashes and adding them all at once makes it faster (at least in Octave, YMMV). The optimized version of record_hashes.m can be found attached. With this alteration the same demo ran in 20s. When caching the data locally the difference is 11.5s to 141s or 12 times faster. The code with all the changes can be found here: Robust Landmark-Based Audio Fingerprinting – optimized for Octave 3.2. Please note again that the implementation is done by Dan Ellis (2009) ( available on Robust Landmark-Based Audio Fingerprinting) and I did only some small tweaks.

Code and HoGent

record_hashes.m.txt and fingerprint_fast.zip

~ Harmony and Variation in Music Information Retrieval

The 29th of February 2012 there was a symposium on Music Information Retreival in Utrecht. It was organized on the occasion of Bas de Haas’ PhD defense. The title of the study day was Harmony and variation in music information retrieval.

During the talk by Xavier Serra rasikas.org was mentioned a forum with discussions about Carnatic Music. Since I could find a couple of discussions about pitch use on that forum I plugged Tarsos there to see if I could gather some feedback.

HoGent and Computational musicology

~ Echo or Delay Audio Effect in Java With TarsosDSP

The DSP library for Taros, aptly named TarsosDSP, now includes an implementation of an audio echo effect. An echo effect is very simple to implement digitally and can serve as a good example of a DSP operation.

The implementation of the effect can be seen below. As can be seen, to achieve an echo one simply needs to mix the current sample i with a delayed sample present in echoBuffer with a certain decay factor. The length of the buffer and the decay are the defining parameters for the sound of the echo. To fill the echo buffer the current sample is stored (line 4). Looping through the echo buffer is done by incrementing the position pointer and resetting it at the correct time (lines 6-9).

  










  
//output is the input added with the decayed echo                 
audioFloatBuffer[i] = audioFloatBuffer[i] + echoBuffer[position] * decay;
//store the sample in the buffer;
echoBuffer[position] = audioFloatBuffer[i];
//increment the echo buffer position
position++;
//loop in the echo buffer
if(position == echoBuffer.length) 
    position = 0;

To test the application, download and execute the Delay.jar file and start singing in a microphone.

The source code of the Java implementation can be found on the TarsosDSP github page.

HoGent, TarsosDSP, Java, and Code

Delay.jar and echo_or_delay_effect.png

~ Spectrogram in Java with TarsosDSP

This is post presents a better version of the spectrogram implementation. Now it is included as an example in TarsosDSP, a small java audio processing library. The application show a live spectrogram, calculated using an FFT and the detected fundamental frequency (in red).

To test the application, download and execute the Spectrogram.jar file and start singing in a microphone.

There is also a command line interface, the following command shows the spectrum for in.wav:

java -jar Spectrogram.jar in.wav

The source code of the Java implementation can be found on the TarsosDSP github page.

Java, Code, HoGent, Computational musicology, and TarsosDSP

spectrogram.png and Spectrogram.jar

~ Démonstration de Tarsos

Nous avons creé une video pour expliquer des possibilités de Tarsos, et maintenant en français.

HoGent, Computational musicology, français, and Tarsos