Op dinsdag vier oktober 2011 werd een les gegeven over bruikbare software voor muziekanalyse. Het doel was om duidelijk te maken welk type onderzoeksvragen van bachelor/masterproeven baat kunnen hebben bij objectieve metingen met software voor klankanalyse. Ook de manier waarop werd besproken: soorten digitale representaties van muziek met voorbeelden van softwaretoepassingen werden behandeld.
Voor de les werden volgende slides gebruikt (ppt, odp):
De behandelde software voor klank als signaal werd al eerder besproken:
Sonic Visualizer: As its name suggests Sonic Visualizer contains a lot different visualisations for audio. It can be used for analysis (pitch,beat,chroma,…) with VAMP-plugins. To quote “The aim of Sonic Visualiser is to be the first program you reach for when want to study a musical recording rather than simply listen to it”. It is the swiss army knife of audio analysis.
BeatRoot is designed specifically for one goal: beat tracking. It can be used for e.g. comparing tempi of different performances of the same piece or to track tempo deviation within one piece.
Tartini is capable to do real-time pitch analysis of sound. You can e.g. play into a microphone with a violin and see the harmonics you produce and adapt you playing style based on visual feedback. It also contains a pitch deviation measuring apparatus to analyse vibrato.
Tarsos is software for tone scale analysis. It is useful to extract tone scales from audio. Different tuning systems can be seen, extracted and compared. It also contains the ability to play along with the original song with a tuned midi keyboard .
music21 from their website: “music21 is a set of tools for helping scholars and other active listeners answer questions about music quickly and simply. If you’ve ever asked yourself a question like, “I wonder how often Bach does that” or “I wish I knew which band was the first to use these chords in this order,” or “I’ll bet we’d know more about Renaissance counterpoint (or Indian ragas or post-tonal pitch structures or the form of minuets) if I could write a program to automatically write more of them,” then music21 can help you with your work.”
Om aan te duiden welke digitale representaties welke informatie bevatten werd een stuk van Franz Liszt in verschillende formaten gebruikt:
The DSP library of Tarsos, aptly named TarsosDSP, now contains an implementation of the Goertzel Algorithm. It is implemented using pure Java.
The Goertzel algorithm can be used to detect if one or more predefined frequencies are present in a signal and it does this very efficiently. One of the classic applications of the Goertzel algorithm is decoding the tones generated on by touch tone telephones. These use DTMF-signaling.
Playing music instruments can bring a lot of joy and satisfaction, but not all apsects of music practice are always enjoyable. In this contribution we are addressing two such sometimes unwelcome aspects: the solitude of practicing and the “dumbness” of instruments.
The process of practicing and mastering of music instruments often takes place behind closed doors. A student of piano spends most of her time alone with the piano. Sounds of her playing get lost, and she can’t always get feedback from friends, teachers, or, most importantly, random Internet users. Analysing her practicing sessions is also not easy. The technical possibility to record herself and put the recordings online is there, but the needed effort is relatively high, and so one does it only occasionally, if at all.
Instruments themselves usually do not exhibit any signs of intelligence. They are practically mechanic devices, even when implemented digitally. Usually they react only to direct actions of a player, and the player is solely responsible for the music coming out of the insturment and its quality. There is no middle ground between passive listening to music recordings and active music making for someone who is alone with an instrument.
We have built a prototype of a system that strives to offer a practical solution to the above problems for digital pianos. From ground up, we have built a system which is capable of transmitting MIDI data from a MIDI instrument to a web service and back, exposing it in real-time to the world and optionally enriching it.
A previous post about PeachNote Piano has more technical details together with a video showing the core functionality (quasi-instantaneous USB-BlueTooth-MIDI communication). Some photos can be found below.
While working on a Latex document with several collaborators some problems arise:
Who has the latest version of the TeX-files?
Which LaTeX distributions are in use (MiKTeX, LiveTex,…)
Are all LaTeX packages correctly installed on each computer?
Why is the bibliography, generated with BiBTeX, not included or incomplete?
How does the final PDF look like when it is build by one of the collaborators, with a different LaTeX distribution?
Especially installing and maintaining LaTeX distributions on different platforms (Mac OS X, Linux, Windows) in combination with a lot of LaTeX packages can be challenging. This blog post presents a way to deal with these problems.
Solution
The solution proposed here uses a build-server. The server is responsible for compiling the LaTeX source files and creating a PDF-file when the source files are modified. The source files should be available on the server should be in sync with the latest versions of the collaborators. Also the new PDF-file should be distributed. The syncing and distribution of files is done using a Dropbox install. Each author installs a Dropbox share (available on all platforms) which is also installed on the server. When an author modifies a file, this change is propagated to the server, which, in turn, builds a PDF and sends the resulting file back. This has the following advantages:
Everyone always has the latest version of files;
Only one LaTeX install needs to be maintained (on the server);
The PDF is the same for each collaborator;
You can modify files on every platform with Dropbox support (Linux, Mac OS X, Windows) and even smartphones;
Compiling a large LaTeX file can be computationally intensive, a good task for a potentially beefy server.
Implementation
The implementation of this is done with a couple of bash-scripts running on Ubuntu Linux. LaTeX compilation is handeled by the LiveTeX distribution. The first script compile.bash handles compilation in multiple stages: the cross referencing and BiBTeX bibliography need a couple of runs to get everything right.
#!/bin/bash#first iteration: generate aux file
pdflatex -interaction=nonstopmode --src-specials article.tex
#run bibtex on the aux file
bibtex article.aux
#second iteration: include bibliography
pdflatex -interaction=nonstopmode --src-specials article.tex
#third iteration: fix references
pdflatex -interaction=nonstopmode --src-specials article.tex
#remove unused files
rm article.aux article.bbl article.blg article.out
The second script watcher.bash is more interesting. It watches the Dropbox directory for changes (only in .tex-files) using the efficient inotify library. If a modification is detected the compile script (above) is executed.
#!/bin/bash
directory=/home/user/Dropbox/article/
#recursivly watch te directorywhile inotifywait -r $directory; do#find all files changed the last minute that match tex#if there are matches then do something...if find $directory -mmin -1 | grep tex; then#tex files changed => recompile
echo "Tex file changed... compiling"/bin/bash $directory/compile.bash
#sleep a minute to prevent recompilation loop
sleep 60
fi
done
To summarize: a user-friendly way of collaboration on LaTeX documents was presented. Some server side configuration needs to be done but the clients only need Dropbox and a simple text editor and can start working togheter.
The Pidato experiment demonstrates a rather straightforward method to handle vibrato on a digital piano. It solves the age-old problem on what to do with the enigmatic “vibrato” instructions on some piano solo scores of Franz Liszt. The figure on the right is an exerpt of sonetto 104 del Petrarca.
Since there is no way to perform vibrato on an analogue piano there are all kinds of different interpretations. Interpretations of the ‘vibrato’ instruction include: vibrating the pedal, vibrating the key, simply ignoring it, a vibrato like wiggling with a psychological sounding effect, … A pianist specialized in 19th century music, explains his embodied use of vibrato in a youtube video: Brian Ganz on piano vibrato. Those solutions all seem a bit halfhearted, so I created an alternative approach which resulted in the Pidato experiment.
Pidato is a portmanteau of piano and vibrato, the d, a and o hint to the use of an Arduino. Pidato is also Indonesian for speech, expression. To get a feel of what it actually does I created the video below. Please note that this is a technical demonstration, not an artistic performance… in any way.
Vid: The Pidato experiment – Vibrato on a Digital Piano using an Arduino.
The way it works is by translating movement (accelerometer data) to MIDI messages. The hardware consists of an Arduino, MIDI-ports and a three axis accelerometer. The MIDI-ports are provided by this MIDI IN & OUT Arduino shield. The accelerometer is a MMA7260Q from Sparkfun. Attaching the MMA7260Q and the arduino is done by following the instructions here. One change was made: by attaching the 3.3V output to AREF and executing analogReference(EXTERNAL); fluctuations in power supply cease to have an influence on accelerometer data readings. It is represented by the purple wire in the diagram below.
The software should know when a vibrato like movement is made and how to translate such movement to MIDI messages. The software therefore contains a periodicity estimator and frequency detector to detect how periodic a movement is and how fast the movement is repeated. This was done with the YIN algorithm (more commonly used in audio signal analysis). A periodicity threshold was determined experimentally so the system does not yield false positives when playing the piano in the usual way. Another interesting bit of code is the interrupt setup that samples the accelerometer at a fixed sample rate and sends MIDI messages, also at a fixed rate.
MIDI messaging is done over a serial connection. From the Arduino sending a MIDI message is as simple as calling Serial.print with the correct data. For the task at hand (sending vibrato) Pitch Bend messages were used. The standard Arduino UNO firmware is replaced with Arduino MIDI firmware. This makes the Arduino appear as a standard MIDI device when connected to a computer, which makes interfacing with it practical.
The YIN algorithm is encapsulated in a reusable Arduino library and can be used to detect periodicity and frequency for any signal. This guy used his implementation to create a chromatic tuner. The source code for both the Yin Arduino library and Pidato experiment can be found on github or here.
The Pidato experiment was done with the help the friendly hackers at Hackerspace Ghent.
Tarsos can be used to render MIDI files to audio (WAV) files using arbitrary tone scales. This functionallity can be used to (automatically) verify tone scale extraction from audio files. Since I could not find a dataset with audio and corresponding tone scales creating one using MIDI seemed a good idea.
MIDI files can be found in spades (for example on piano-midi.de or kunstderfuge.com), tone scales on the other hand are harder to find. Luckily there is one massive source, the Scala Tone Scale Archive: A large collection of over 3700 tone scales.
Using Scala tone scale files and a midi files a Tone Scale – Audio dataset can be generated. The quality of the audio depends on the (software) synthesizer and the SoundFont used. Tarsos currently uses the Gervill synthesizer. Gervill is a pure Java software synthesizer with support for 24bit SoundFonts and the MIDI tuning standard.
How To Render MIDI Using Arbitrary Tone Scales with Tarsos
A recent version of the JRE needs to be installed on your system if you want to use Tarsos. Tarsos itself can be downloaded in the form of the MIDI and Scala to Wav – JAR Package.
To test the program you can use a MIDI file and a Scala file and drag and drop those on the graphical interface.
The result should sound like this:
To summarize: by rendering audio with MIDI and Scala tone scale files a dataset with tone scale – audio information can be generated and tone scale extraction algorithms can be tested on the fly.
This is about PeachNote Piano, a project only tangentially related to Tarsos. PeachNote Piano aims to capture as many piano practice sessions as possible and offer useful services using this data. The system does this by capturing and redirecting MIDI events on a Bluetooth enabled smartphone. It is done together with Vladimir Viro and builds on the existing PeachNote infrastructure.
The schema – right – shows the components of the PeachNote Piano system. At the bottom you have a MIDI keyboard connected to the MIDI-Bluetooth-bridge. A smartphone (middle left) receives these MIDI events via Bluetooth and controls the communication to the server (top left). An alternative path goes through a standard computer (top right).
The Arduino based Bluetooth to MIDI bridge is an improvement on the work by Peter Brinkmann. The video below shows communication between USB-MIDI, Bluetooth MIDI and MIDI IN/OUT ports.
As an example application of the PeachNote Piano system we implemented a “Continue a Melody” service which works as follows: a user plays something on a keyboard, maybe just a few notes, and pauses for a few seconds. In the meantime, the server searches through a large database of MIDI piano recordings, finds the longest fuzzy match for the user’s most recent input, and, after a short silence on the users part, starts streaming the continuation of the best matched performance from the database to the user. This mechanism, in fact, is way of browsing a music collection. Users may play a known leitmotiv or just improvise something, and the system continues playing a high quality recording, “replying” to the musical proposition of the user.
More technical details
The melody matching is done on the server, which is implemented in Javascript in the Node.js framework. The whole dataset (about 350 hours of piano recordings) resides in memory in two representations: as a sequence of pitches, and as a sequence of “densities” at the corresponding places of the pitch sequence dataset. This second array is used to store the rough tempo information (number of notes per second) absent in the pitch sequence data.
By combining the two search criteria we can achieve reasonable approximation of the tempo-aware search without its computational complexity.
The implementation of the hardware is based on the open-source electronic prototyping platform Arduino. Optocoupled MIDI ports (IN/OUT) and the BlueSMiRF Bluetooth module were attached to the main board, as can be seen in the middle left block of the schema. The BlueTooth module is configured to use the Serial Port Profile (SPP) which emulates RS-232. The software on the Arduino manages bi-directional, low latency message passing between three serial ports: USB (through an FTDI chip), BlueTooth and the hardware MIDI-IN and OUT port.
The standard Arduino firmware has been replaced with firmware that implements the “Universal Serial Bus Device Class Definition for MIDI Devices”: when attached to a computer via USB, the Arduino shows up as a standard MIDI device, which makes it compatible with all available MIDI software. The software client currently works on the Android smartphone platform. It is represented using the middle right block in the schema. The client can send and receive MIDI events over its Bluetooth port. Pairing, connecting and communicating with the device is done using the Amarino software library. The client communicates with the Peachnote Piano server using TCP sockets implemented on the Dalvik Java runtime.
This article describes how to do makam recognition with a script that uses the Tarsos API.
The task we want to do is to find the tone scales most similar to the one used in recorded music. To complete this task you need a small set of theoretical scales and a large set of music, each brought in one of the scales. To make it more concrete, an example of Turkish classical music is used.
In an article by Bozkurt pitch histograms are used for – amongst other tasks – makam recognition. A maqam defines rules for a composition or performance of classical Turkish music. It specifies melodic shapes and pitch intervals, the scale. The task is to identify which of nine makams is used in a specific song. A simplified, generalized implementation of this task is shown here. In our implementation there is no tonic detection step. Also here we use only theoretical descriptions of the tone scales as a template and do not construct a template using the audio itself, as is done by Bozkurt. Ioannidis Leonidas wrote an interesting master thesis about makam recognition. Since no knowledge of the music itself is used the approach is generally applicable.
The following is an implementation in Scala a general purpose programming language that is interoperable with Jave . The first step is to write the Scala header. This is just some boilerplate code to be able to run the script from the command line – it assumes a UNIX-like environment and tarsos.jar in the same directory:
The second step constructs the templates the capability of Tarsos to create
theoretical tone scale templates using Gaussian kernels is used, line 8. See the attached images for some examples.
val makams = List( "hicaz","huseyni","huzzam","kurdili_hicazar",
"nihavend","rast","saba","segah","ussak")
var theoreticKDEs = Map[java.lang.String,KernelDensityEstimate]()
makams.foreach{ makam =>
val scalaFile = makam + ".scl"
val scalaObject = new ScalaFile(scalaFile);
val kde = HistogramFactory.createPichClassKDE(scalaObject,35)
kde.normalize
theoreticKDEs = theoreticKDEs + (makam -> kde)
}
The third and last step is matching. First a list of audio
files is created by recursively iterating a directory and matching each file to
a regular expression. Next, starting from line 4, each audio file is processed.
The internal implementation of the YIN pitch detection
algorithm is used on the audio file and a pitch class histogram is created
(line 6,7). On line 10 normalization of the histogram is done, to
make the correlation calculation meaningful. Line 11 until 15 compare the
created histogram from the audio file with the templates calculated beforehand.
The results are stored, ordered and eventually printed on line 19.
val directory = "/home/joren/turkish_makams/"
val audio_pattern = ".*.(mp3|wav|ogg|flac)"
val audioFiles = FileUtils.glob(directory,audio_pattern,true).toList
audioFiles.foreach{ file =>
val audioFile = new AudioFile(file)
val detectorYin = PitchDetectionMode.TARSOS_YIN.getPitchDetector(audioFile)
val annotations = detectorYin.executePitchDetection()
val actualKDE = HistogramFactory.createPichClassKDE(annotations,15);
actualKDE.normalize
var resultList = List[Tuple2[java.lang.String,Double]]()
for ((name, theoreticKDE) <- theoreticKDEs){
val shift = actualKDE.shiftForOptimalCorrelation(theoreticKDE)
val currentCorrelation = actualKDE.correlation(theoreticKDE,shift)
resultList = (name -> currentCorrelation) :: resultList
}
//order by correlation
resultList = resultList.sortBy{_._2}.reverse
Console.println(file + " is brought in tone scale " + resultList(0)._1)
}
An oral presentation about Tarsos is going to take place Tuesday, the 25 of October during the afternoon, as can be seen on the ISMIR preliminary program schedule.
If you want to cite our work, please use the following data:
@inproceedings{six2011tarsos,
author = {JorenSixandOlmoCornelis},
title = {Tarsos - a Platform to ExplorePitchScalesinNon-WesternandWesternMusic},
booktitle = {Proceedings of the 12th InternationalSocietyforMusicInformationRetrievalConference,
ISMIR2011},
year = {2011},
publisher = {InternationalSocietyforMusicInformationRetrieval}
}
I have upgraded the operating system on my LG GT540 Optimus from the stock Android 1.6 to Android Gingerbread 2.3.4. I followed this updgrade procedure.
It is well worth it to spend some time upgrading the phone, especially from 1.6. Everything feels a lot faster and the upgraded applications, e.g. Gallery, are nicely improved.
The main reason I upgraded my phone is to get the open source accessory development kit (ADK) for Android working. I got the DemoKit application working after some time but need to do some more experiments to see if the hardware actually works: I am waiting for a USB Host Shield for Arduino. To be continued…
Tarsos, a software package to analyse pitch organization in music, contains a new output modality. It is now possible to export a pitch class histogram and a pitch class interval matrix to latex from within Tarsos. This makes documenting tone scales more efficient.
Tarsos, a software package to analyse pitch organization in music, contains a new output modality. Now it is possible to export resynthesized pitch annotations, detected by a pitch detection algorithm and compare those with the original sound. This can be interesting to see which errors a pitch detection algorithm makes.
Below you can listen to an example of synthesized pitch detection results compared with the original flute piece. The file starts with only the original flute sound (on the right channel) and gradually changes so only the synthesized annotations (on the left channel) can be heard.
The 25th of May 2011 Tarsos was present at the IPEM open house.
IPEM (Institute for Psychoacoustics and Electronic Music) is the research center of the Department of Musicology, which is part of the Department of Art, Music and Theater Studies of Ghent University. IPEM provides a scientific basis for the cultural and creative sector, especially for music and performance arts, and does pioneering research work on the relationship between music body movement and new technologies. The institute consists of an interdisciplinary team but also welcomes visiting researchers from all over the world. One of its aims is also to actively try and validate research results during public events and by means of user studies.
This article describes how to make sun-java6 play nice with the PulseAudio sound sytem on Ubuntu with an x64 processor architecture. With some changes the method should also work with other operating systems and other platforms.
The default way sun-java6 operates with respect to sound on Ubuntu is, well unrespectfull. When playing audio it claims an audio device, which then can not be used any more by other applications trying to access the same device. This is far from ideal. Also changing audio interfaces (by e.g. plugging in a USB audio interface) goes wrong most of the time.
These problems are addressed by PulseAudio and there is a way to make sun-java6 aware of PulseAudio on Ubuntu. The OpenJDK does this automatically but it has some other, unrelated, issues. If you want to use PulseAudio with java6 on Ubuntu x64 you need copy pulse-java.jar and platform dependent libpulse-java.so file to correct JVM directories. To make it easy you can execute these commands:
From this moment on the “PulseAudio Mixer” is available for Java applications. Sharing, switching and assigning audio devices to Java programs is as a result smooth. To use the PulseAudio Mixer by default you need to change sound.properties which can be found at /usr/lib/jvm/java-6-sun/jre/lib/sound.properties. Details can be found here.
Vorige zaterdag werd Apps For Ghent georganiseerd: een activiteit om het belang van open data te onderstrepen in navolging van onder meer Apps For Amsterdam en New York City Big App. Tijdens de voormiddag kwamen er verschillende organisaties hun open gestelde data voorstellen de namiddag werd gereserveerd voor een wedstrijd. Het doel van de wedstrijd was om in enkele uren een concept uit te werken en meteen voor te stellen. Het uitgewerkte prototype moest gedeeltelijk functioneren en gebruik maken van (Gentse) open data.
Luk Verhelst en ikzelf hebben er TwinSeats voorgesteld.
TwinSeats is een website / online initiatief om nieuwe mensen te leren kennen. Met hen deel je dezelfde culturele interesse en ga je vervolgens samen naar deze of gene voorstelling. Door events centraal te stellen kan TwinSeats uitzonderlijke cultuurburen zoeken. Leden vinden die cultuurburen dankzij een gezamenlijke voorliefde voor een artiest of attractie of eender welke bezigheid in de vrijetijdssfeer.
Het prototype is ondertussen terug te vinden op TwinSeats.be. Let wel dit is in enkele uren in elkaar geflanst en is verre van ‘af’, het achterliggende concept is belangrijker.
“The First International Workhop of Folk Music Analysis: Symbolic and Signal Processing, will take place in Athens, Greece, on the 19th and 20th of May, 2011. … The purpose of the event is to gather reseachers who work in the area of computational folk music analysis, using symbolic or singal processing methods, to present their work, discuss and exchange views on the topic.”
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.
Its aim is to provide a simple interface to some audio (signal) processing algorithms implemented in JAVA.
To make some of the possibilities clear I coded some examples.
Tarsos is een softwareprogramma waarmee toonhoogte in muziek onderzocht kan worden in onder meer etnische muziek. Het kan gebruikt worden om toonintervallen en toonladders te identificeren. Het maakt kwarttonen of andere (ongewone) intervallen visueel duidelijk. Tarsos heeft nu ook real-time mogelijkheden. Geluid afkomstig van een microfoon wordt meteen geanalyseerd en onmiddellijke feedback toont een gespeeld of gezongen interval. Zangers of instrumentalisten die willen experimenteren met intonatie kunnen Tarsos zelf uit te proberen.
Meer info over de werking van Tarsos is te vinden in een kort artikel over de werking van Tarsos. Daarin wordt ook de betekenis van de verschillende vensters in Tarsos duidelijk.
Installatie
Om Tarsos te kunnen gebruiken heb je, naast Tarsos zelf, Java nodig. Java staat waarschijnlijk al op je pc. Dit is te controleren op java.com. Daar zijn ook instructies te vinden hoe je Java kan installeren.
Met een werkende Java is Tarsos installeren eenvoudig: download Tarsos en voer het uit (dubbel klikken).
Toonladder detecteren
Om een toonladder te detecteren in een muziekbestand met Tarsos doe je het volgende.
Detecteer de pieken in het histogram door met de slider peakpicking te bewegen. Als niet alle pieken gedetecteerd worden kan je een piek toevoegen door met alt en een muisbeweging over het pitch class histogram te bewegen. Klik om de positie van de piek te bevestigen. Met ctrl kunnen pieken verplaatst worden.
Deze stappen zijn ook te zien in een screenshot in de bijlage. Om de informatie te exporteren kan je bij de uitvoeropties kijken. Met file - export - scala... kan je een scala bestand exporteren. Dit zijn tekstbestanden met daarin een toonladder die gebruikt kunnen worden in het Scala programma.
Real time analyse
Met de real time analyse kan je intervallen inspelen en via visuele feedback meteen te weten komen hoe dicht je intonatie bij het gewenste resultaat zat. Je hebt er een microfoon voor nodig. Door Settings - Tarsos Live te kiezen en daarna Tarsos af te sluiten en opnieuw te starten luistert Tarsos naar geluid afkomstig van een microfoon. Speel toonhoogte intervallen en die worden visueel duidelijk. De reset knop wist het histogram.
Tijdens ARIP wordt Tarsos voorgesteld en kan het zelfs uitgetest worden. Volgens de ARIP website : “Op 18 maart 2011 stellen de verschillende onderzoekers hun onderzoeksproject voor: geen afgewerkte producten of eindresultaten, maar wel momentopnames. Samen bieden ze een interessante en intrigerende kijk in wat het onderzoek in ons Conservatorium te bieden heeft”.
Het tekstje over Tarsos:
Tarsos is een softwareprogramma waarmee toonhoogte in muziek onderzocht kan worden in onder meer etnische muziek. Tarsos heeft nu ook nieuwe, real-time mogelijkheden. Geluid afkomstig van een microfoon wordt meteen geanalyseerd en onmiddellijke feedback toont een gespeeld of gezongen interval. Het maakt kwarttonen of andere (ongewone) intervallen visueel duidelijk.
Tijdens ARIP zal er kort wat uitleg gegeven worden over Tarsos en mag je een demo verwachten. Zangers of instrumentalisten die willen experimenteren met intonatie zijn ook meer dan welkom om Tarsos zelf uit te proberen.
This monday the 28th of February Tarsos will be presented at “Lectures on Computational Ethnomusicology” which is held at Izmir, Turkey. The presentation of Tarsos is available here.
Next to the interesting programme it is a great opportunity to meet Baris Bozkurt who has been working on similar research but applied to Makam music.
On wednesday the second of March there is a small seminar at Electrical and Electronics Eng. Dept. of İzmir Yüksek Teknoloji Enstitüsü where Tarsos will be presented also.
HoGent
01.musicXML-liebestraum_no_3.xml, 00.partituur.liebestraum_3.pdf, 2011.10.04.bruikbare_software_voor_muziekanalyse.ppt, 2011.10.04.bruikbare_software_voor_muziekanalyse.odp, 01.BeatRoot.tempo.wav, beatroot-0.5.8-rc1.jar, 03.human.performance.wav, 02.performed_midi.wav, and 01.deadpan_midi.wav
The extended abstract about PeachNote Piano has been accepted as a demonstration presentation to appear at the 
While working on a Latex document with several collaborators some problems arise:
The Pidato experiment demonstrates a rather straightforward method to handle vibrato on a digital piano. It solves the age-old problem on what to do with the enigmatic “vibrato” instructions on some piano solo scores of Franz Liszt. The figure on the right is an exerpt of 
A paper about Tarsos was submitted for review at the 
The 25th of May 2011 Tarsos was present at the 
TwinSeats is een website / online initiatief om nieuwe mensen te leren kennen. Met hen deel je dezelfde culturele interesse en ga je vervolgens samen naar deze of gene voorstelling. Door events centraal te stellen kan TwinSeats uitzonderlijke cultuurburen zoeken. Leden vinden die cultuurburen dankzij een gezamenlijke voorliefde voor een artiest of attractie of eender welke bezigheid in de vrijetijdssfeer.
