Sight-playing – part 3

to play like a sheet music

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We already created the harmony of the piece in the previous article. What we need now is a good melody which will match this harmony. Melodies consist of motifs, i.e. small fragments of about 2-5 notes and their variations (transformations).

We will start by generating the first motif – its rhythm and sounds. As we did when generating the harmony, we will use N-gram statistics for musical pieces. Such statistics will be prepared using the Essen Folksong Collection base. You might as well use any other melody base, this choice will affect the type of melodies that will be generated. For each piece, we must isolate the melody, convert it into a sequence of rhythmic values and a sequence of sounds, and from these sequences extract the statistics. When compiling sound statistics, it is a good idea to first somehow prepare the melodies – transpose them all to two keys, e.g. C major and c minor. This will reduce the number of possible (probable) N-grams by 12 times and therefore the statistics will be better assessed.

A good motif

We will begin creating the first motif by generating its rhythm. Here, I would like to remind you that we have previously made a certain simplification – each motif and its variations will last exactly one bar. The subsequent steps for generating the rhythm of a motif: – we draw the first rhythmic value using unigrams, – we draw the next rhythmic value using bigrams and unigrams, – we continue to draw consecutive rhythmic values, using N-grams of increasingly higher level (up to 5-grams), – we stop until we reach a total rhythmic value equal to the length of one bar – if we have exceeded the length of 1 bar, we start the whole process from the beginning (such generation is fast enough that we can afford such a sub-optimal trial-and-error method).

The next step is to generate the sounds of the motif. Another simplification we made earlier is that we generate pieces only in C major key, so we will make use of the N-gram statistics created on the basis of pieces transposed to this key, excluding pieces in minor keys. The procedure is similar to that for generating rhythm: – we draw the first sound using unigrams, –we draw the next sound using bigrams and unigrams, – we continue until we have drawn as many sounds as we have previously drawn rhythmic values, – we check whether the motif matches the harmony, if not, we go back and start again – if after approx.

100 attempts we failed to generate a motif matching the harmony, this could mean that with the preset harmony and the preset motif there is a very low probability of drawing sounds that will match the harmony. In this case, we go back and generate a new motif rhythm.

Generate until you succeed

When generating both the motif rhythm and its sounds, we use the trial-and-error method. It will also be used in the generation of motif variations described below. Even if this method may seem “stupid”, it’s simple and it works. Although very often such randomly generated motifs don’t match the harmony, we can afford to make many such mistakes. Even 1000 attempts take a short time to calculate on today’s computers, and this is enough to find the right motif.

Variations with raepetitions

We have the first motif, and now need the rest of the melody. However, we will not continue to generate new motifs, as the piece would become chaotic. We also cannot keep repeating the same motif, as the piece would become too boring. A reasonable solution would be, in addition to repeating the motif, to create a modification of that motif, ensuring variation, but without making the piece chaotic.

There are many methods to create motif variations. One such method is chromatic transposition. It involves transposing all notes upward or downward by the same interval. This method can lead to a situation where a motif variation has sounds from outside the key of the piece. This, in turn, means that the probability that the variation will match the harmony is very low. Another method is diatonic transposition, whereby all notes are transposed by the same number of scale steps. Unlike the previous method, diatonic variations do not have off-key sounds.

Yet another method is to change a single interval; one of the motif intervals is changed, while all other intervals remain unchanged. That way, only one part of the motif (the beginning or the end) is transposed (via chromatic or diatonic transposition). Further methods are to convert two notes with the same rhythmic value to one or to convert one note to two notes with the same rhythmic value. For the first method, if the motif has two notes with the same rhythmic value, its rhythm can be changed by combining these two notes. For the second method, a note is selected at random and converted to two “shorter” notes.

Each of the described methods for creating variations makes it possible to generate different motifs. The listed methods are not the only valid methods; it is possible to come up with many more. The only restriction here is that the generated variation should not differ too much from the original motif. Otherwise, it would constitute a new motif rather than a variation. The border where the variation ends and a different motif begins is conventional in nature.

Etc., etc.

There are many more methods for generating motif variations; it is possible to come up with a lot of these. The only restriction is that the generated variation should not differ too much from the original motif. Otherwise, it would constitute a new motif rather than a variation. The border where the variation ends and another motif begins is rather conventional in nature and everyone “feels”, defines it a little differently.

Is that all?

That would be all when it comes to piece generation. Let us summarise the steps that we have taken:

  1. Generating piece harmony:
    • generating harmonic rhythm,
    • generating chord progression.
  2. Generating melody:
    • generating motif rhythm,
    • generating motif sounds,
    • creating motif variations,
    • creating motifs and variations “until it’s done”, that is, until they match the generated harmony

All that is left is to make sure that the generated pieces are of the given difficulty, i.e. matching the skills of the performer.

Controlling the difficulty

One of our assumptions was the ability to control the piece difficulty. This can be achieved via two approaches:

  1. generating pieces “one after another” and checking their difficulty levels (using the methods described earlier), thereby preparing a large database of pieces from which random pieces of the given difficulty will then be selected,
  2. controlling the parameters for creating the harmonies, motifs and variations in such a way that they generate musical elements of the given difficulty with increased frequency

Both methods are not mutually exclusive and thus can be successfully used together. First, a number of pieces (e.g. 1000) should be generated randomly, and then parameters should be controlled to generate further pieces (but only those which are missing). With respect to parameter control, it is worth noting that the probability of motif repetition can be changed. For pieces with low difficulty, the assigned probability will be higher (repetitions are easier to play). On the other hand, difficult pieces will be assigned lower probability and rarer harmonies (which will also force rarer motifs and variations).

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