Download Paper - Piano Sound database PianoUPM

A piano sound database for testing automatic
transcription methods
Luis Ortiz-Berenguer, Elena Blanco-Martin, Alberto Alvarez-Fernandez, Jose A. Blas-Moncalvillo,
Francisco J. Casajus-Quiros
1
Universidad Politecnica de Madrid, Spain
Correspondence should be addressed to Luis Ortiz-Berenguer ([email protected])
ABSTRACT
A piano sound database, called PianoUPM, is presented. It is intended to help the researching community
in developing and testing transcription methods. A practical database needs to contain notes and chords
played through the full piano range and it needs to be recorded from acoustic pianos rather than synthesized
ones. The presented piano sound database includes the recording of 13 pianos from different manufacturers.
There are both upright and grand pianos. The recordings include the eighty-eight notes and eight different
chords played both in legato and staccato styles. It also includes some notes of every octave played with four
different forces to analyze the nonlinear behavior. This work has been supported by the Spanish National
Project TEC2006-13067-C03-01/TCM.
1. INTRODUCTION
Music Information Retrieval (MIR) involves a lot
of issues. Automatic transcription is an application
requiring identification of the played notes among
its tasks. Some transcription methods make use of a
previous training stage. Sound databases are necessary tools when developing and testing transcription
algorithms.
In this work, a piano sound database is presented.
The goal of this database is to help researchers in de-
veloping transcription algorithms oriented to piano
music. Piano transcription is a challenging task due
to the clearly different behavior of the instrument
depending on the octave being played and the force
applied to the keyboard. One of the more noticeable
differences is the spectrum of the sound. A practical
database needs to contain notes and chords played
through the full piano range (i.e., from A0 to C8)
and be recorded from acoustic pianos rather than
synthesized ones.
Ortiz-Berenguer et al.
Piano sound database
Fig. 1: Plots show spectra of the chord CEG played in three different octaves using two forces. Octave
modifies the spectral content regarding the number of partials and spectral envelope. Force increases nonlinear distorsion, some new spectral components appear due to Inter-Modulation products, shown as a partial
widening because of low spectral resolution.
2. THE DATABASE
The presented piano sound database includes the
recording of 13 pianos from different manufacturers.
Some of them are upright and some are grand pianos.
The recordings of every piano include the following
sounds:
4. Two off-octave-long-4-note-chords (the last
note, marked +, belongs to the next octave):
(a) CGA#E+.
(b) CEGC+.
1. The eighty-eight notes without releasing the key
to obtain a note as long as the piano gets.
The above described recordings were performed
playing softly the keys to reduce the effect of nonlinear distortion produced by the hammer strike.
2. Two 3-note-chords (i.e., triads) played without
releasing the key (we call them long chords).
They are:
2.1. Recordings for testing non-linearity
To analyze the effect of non-linearity, the database
also includes the following recordings:
(a) CEG.
(b) CD#G.
As far as all notes belong to the same octave,
we call them in-octave chords.
3. Four in-octave-long-4-note-chords (tetrads):
1. The same eight previous chords played in staccato style, with a fast attack and releasing the
keys, leading to a short duration version of
the chords, due to the activation of the string
dampers.
2. Every A note (from A0 to A7) played using four
different forces (from pianissimo to forte)
(a) CEGA#.
(b) CD#F#A.
(c) CD#GA#.
(d) CDGB.
2.2. Melodies and onset detection
Some of the piano recordings also include a performed simple melody to test the transcription including onset detection or segmentation. Also, a
Ortiz-Berenguer et al.
Piano sound database
two-handed version of that melody is included in
some pianos to test a more real situation.
database will be available free of charge to the researching community in the following web page:
http://pianoupm.euitt.upm.es/database.htm
3. METHOD FOR CREATING THE DATABASE
A pianist was in charge of the performances. Being
the keys pianist-played rather than mechanicallyexcited increases the variability of the parameters to
be analyzed by the algorithms but also increases the
similarity of the database sounds to the real sounds
to be transcribed afterwards. Played sounds were
picked-up by a studio-quality condenser microphone
from AKG and recorded on a professional-grade Digital Audio Tape from Sony. Peak-metering was
strictly controlled to avoid distortion during AtoD
conversion. Pianos had been tuned by a professional
tuner, prior to the recording sessions, except one of
them. Thus, the database also allows to analyze the
efficiency of transcription methods on mistuned pianos. The DAT tapes were transferred to a DAW,
where every element of the database (either note or
chord) was isolated and saved as a .wav file.
The database is organized in folders. Every folder
corresponds to one piano. The name of the folder includes the brand, model, type of piano (’g’ for grand
or ’u’ for upright) and an ID code that is also used
in the sound files.
The recorded piano are shown in table 1.
Melodies sub-folder has sound files which name indicates the melody ID and the piano ID.
Type
Grand
Grand
Grand
Grand
Grand
Grand
Grand
Upright
Upright
Upright
Upright
Upright
Upright
Brand
Steinway
Schimmel
Schimmel
Schimmel
Kawai
Kawai
Kawai
Schimmel
Schimmel
Kawai
Kawai
Pleyel
Pleyel
Model
Model D
256
213T
GP169T
ShigeruKawai
RX2
GE30
116s
112KE
K18
K80
Academie
P124
For every piano there are up to four sub-folders:
Notes, Chords, ’IM’ and Melodies.
Notes sub-folder contain 88 ’wav’ files. The name
of ’wav’ files include note identification, octave and
piano ID code.
The name of ’wav’ files inside the Chords sub-folder
contains chord ID, octave, type of playing and piano
ID code.
In the case of ’IM’ subfolder, the files name includes
the ’im’ code, force indicator, note, octave and piano
ID.
5.
CONCLUSIONS
A
sound
database
is
available
at
http://pianoupm.euitt.upm.es/database.htm,
which contains recordings of 13 different acoustic
pianos from several manufacturers. This database
can be utilized to develop and test transcription
algorithms. It contains single notes as well as
chords of several types and performed differently.
Each element is recorded as a .wav file to allow full
compatibility and worldwide interchangeability.
6. ACKNOWLEDGEMENTS
This work has been supported by the Spanish National Project TEC2006-13067-C03-01/TCM.
Table 1: Recorded pianos for the database
7.
4. RESULTS
The results of this work have been a set of recordings organized as a database called PianoUPM. It
has already been used to develop and test transcription algorithms which were reported in previously published works(1). From now on, this
REFERENCES
[1] L.I.Ortiz-Berenguer, F.J. Casajus-Quiros,
E.Blanco-Martin. An improved pattern-matching
method for piano multi-pitch detection 124th AES
Convention. Paper 7383. May 2008. Amsterdam.
The Netherlands.