04. Erstarrung. (Numbness)
Modified strophic form in c minor containing five stanzas. [more]
Normalized variant of the well-known MFCC features (3 sec), the low bands are loosely correlated to timbre. [more]
Singer: Randall Scarlata (Baritone), Piano: Jeremy Denk. Recording of a performance at the Isabella Stewart Gardner Museum, Boston.
Source, License: CC BY-NC-ND 2.0
Information about our segmentation of »04. Erstarrung«
Modified strophic form in c minor containing five stanzas.
Coarse segmentation as ternary form ABA'.
The first part consists of the segments I1, A, B, and C1 of the given fine-granular segmentation.
In this case, A and B are the first stanza of the poem and its repetition.
The instrumental introduction I1 as well as the sung part A are in c minor. Segments B and C1 are in e flat minor and g minor, respectively.
Its middle part (D in segmentation) has an instrumental prelude lasting four measures. The part itself is in A flat major, and corresponds to the third stanza of the poem.
The song's last part is a modified variant of its first part without interlude. Instead, a coda (I3) in c minor is appended.
Segments A and B following D cover the fourth stanza and its repetition. C2 is the last stanza.
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.