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17. Im Dorfe. (In the Village)

feature MFCCLOW representation

Piece:

17. Im Dorfe

Variiertes Strophenlied in D-Dur mit zwei Strophen. [more]

Musical aspect/feature:

timbre/MFCC-ENS

Normalized variant of the well-known MFCC features (3 sec), the low bands are loosely correlated to timbre. [more]

Recording:

European archive: Hüsch, 1933

Singer: Gerhard Hüsch (Baritone), Piano: Hanns-Udo Müller. Recorded on vinyl, April-September 1933.

Source, License: EA Terms of Use

Information about our segmentation of »17. Im Dorfe«

Variiertes Strophenlied in D-Dur mit zwei Strophen.
Die Segmentierung entspricht im Wesentlichen der Stropheneinteilung, wobei auf jede Textstrophe zwei musikalische Segmente fallen.
Die musikalische Struktur des Liedes lässt drei verschiedene Segmente erkennen: A, B und C, wobei nur A im Laufe des Stücks wiederholt wird.
Die Wiederholung von A variiert in der zweiten Hälfte, daher müsste das zweite Vorkommen von A eigentlich A' heißen.
Man könnte A auch in A1 (T.6-11) und A2 (T.12-19) und A' in A1 (T.30-35) und A3 (T.36-37) unterteilen, oder nur zwischen A und A' (d.h. A1 und A2) ohne weitere Unterteilung unterscheiden.
Die Strophe C ist in der Melodik und in der Harmonik näher an A als B an A.

Lyrics: Project Gutenberg

MFCC (Mel Frequency Cepstral Coefficients)

This feature was originally developed for speech analysis and speaker recognition. After transforming a musical signal in a spectrogram representation, MFCC-based features are computed by combining suitable frequency bands into percepually inspired Mel bands and applying a decorrelating discrete cosine transformation. Especially, the lower MFCC bands describe the coarse form of the spectral envelope which correlates to timbre. For deriving MFCC-ENS features (MFCC Energy Normalized Statistics), these MFCC features are quantized, smoothed (in temporal direction), and normalized with respect to the ℓ2-norm.

Furthermore, we present a novel variant of MFCC-ENS features by prior weighting the spectrogram by the second derivative of the spectral phase information in the time domain. This indicates slight changes in pitch which typically occur in vocals and which are not present in piano music. Especially the harmonics of piano-played notes are attenuated by this method which leads to smaller spectral envelopes in the piano sections and hence to more discriminative timbre-related MFCC features.

Literature

  • Steven Davis, Paul Mermelstein: Comparison of parametric representations for monosyllabic word recognition in continuously spoken sentences, Readings in Speech Recognition 1990, pp. 65–74.
  • Hiroko Terasawa, Malcolm Slaney, Jonathan Berger: The thirteen colors of timbre, WASPAA 2005, pp. 323–326.
  • Dirk v. Zeddelmann, Frank Kurth: A construction of compact MFCC-type features using short-time statistics for applications in audio segmentation, EUSIPCO 2009, pp. 1504–1508.