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Bach Cantatas Vol. 10

Introduction English This is a setting that, like others, manages to combine a large variety of musical ideas in a short span. Opening with an introduction of long semibreves, the metre eventually increases to crotchets and, after the chorale enters, occasional quavers. The chorale is heard in canon between the soprano and tenor. Two other versions of the melody in the middle of the 17 th century are 1.


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  2. Strengthen for service, Lord the hands.
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This is an important reference source used by the NBA to show the shape and form of the chorale melody as Bach might have known it. Text : Ach Gott und Herr EKG : There are two likely prospects for the author of the chorale text It is not clear why the dates for the first publication of the text differ. Later, in , he became superintendent and Professor of Theology at the University of Jena.

Perhaps Rutilius and Major were co-authors, or perhaps Major later added verses to Rutilius original, shorter version, a not uncommon practice at the time.

Fugue on Ach Gott Und Herr-Organ by BANNWART, J| J.W. Pepper Sheet Music

Peter Williams, on p. The NBA has not published these works and they have appeared in published collections of chorale preludes by Johann Gottfried Walther since the beginning of the 20 th century. The asterisk indicates the true polyphony. Figure 4. Polyphony estimation results.

Given pitches estimates in individual frames, we view the pitch streaming problem as a clustering problem. The instances are the pitch estimates, and each cluster corresponds to a source. Inspired by the fact that human use timbral information to follow a sound source, we define the clustering objective as minimizing the timbral inconsistency within each cluster. Therefore, we need a timbral feature vector for each pitch estimate. We explore several kinds of timbral features. For musical instruments, we showed in a previous paper DuanEtal'08 that harmonic structure relative log-amplitudes of harmonics is an appropriate feature.

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The MFCC feature is calculated from the separated signal of each talker, after a simple but inaccurate source separation step of the mixture audio frame. The UDC feature is what we newly proposed. It can be calculated from several isolated spectral points in the mixture signal, without requiring source separation.

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Strengthen for Service Lord the Hands - Ach Gott Und Herr (Instrumental Version)

Then the clustering can be done by K-means. However, results are not good. Figure 4 gives an example. This is a duet of saxophone red circles and bassoon black dots. In the streaming results, we can see that a number of pitches are clustered into wrong trajectories.

What is it good for?

For example, the pitches around MIDI number 55 from Another example, from This is not reasonable, since saxophone is a monophonic instrument. The first error should not be too hard to remove, if we assume that pitches form a continuous contour come from the same source.


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  • The second error can also be removed if we do not allow simultaneous pitches to be in the same cluster. Therefore, we add two kinds of constraints to the clustering problem:. Timbral information is not enough to achieve good pitch streaming.


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    • The constrained clustering problem formulated above has the following properties, which make existing algorithms do not apply:. We propose a novel constrained clustering algorithm, which monotonically decreases the objective function, and incrementally satisfy more constraints.