Relevant strengths that appeared in this task were that after selection of the music piece, it was narrowed down to the main chorus, which contains repeating sequences of notes.
Although it does not follow a similar pattern, it can be refined further to act as an algorithm.
The final model is not applicable to real-life applications of mathematics, as shown in the different number of notes and use of the Markov chain in nature, where transition probability does not change.
The final tune does not seem practical in real life as it solely relies on an Excel random note generator. Matrix is a suitable method for music composition, but it may not be the most accurate as it may not capture all aspects of musical expression as it is only based on the probability of future notes.
Utilising the Markov chain model fits the criteria of complexity but is not the best approach, as unexpected predictions happen too often in the process of random note generation. It seemed that Markov chains were better at generating melody than chords that have more than one note and are harder to generate. can you make them into one pargaph seperating strengh and limtaion
One relevant strength of this task is the ability to narrow down the selection of the music piece to the main chorus, which contains repeating sequences of notes. This provides a clear focus and simplifies the process of creating the algorithm.
However, the final model's limitations become apparent when considering real-life applications of mathematics. The different number of notes and the use of Markov chains, where transition probabilities do not change, indicate that this model may not accurately represent real-life music composition scenarios.
Additionally, the final tune generated solely relies on an Excel random note generator, which doesn't seem practical in real-life music production. While the matrix method used for music composition is suitable, it may not capture all aspects of musical expression since it is solely based on the probability of future notes.
The use of a Markov chain model adds complexity to the task, but it may not be the most effective approach. The frequent occurrence of unexpected predictions in the process of random note generation suggests that the Markov chains excel at generating melodies rather than chords that involve multiple notes and are more challenging to generate.