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In this study the authors looked at the ability of the Discrete Fourier Transform (DFT) to analyze different musical elements. They found that DFT is a powerful method to analyze recorded music.

Here, the researchers investigated how exposure to active versus passive music affects a teenager's ability to perform a challenging task, namely a Sudoku puzzle, under stressful conditions. Following testing 75 high school teenagers split into two group, the researchers found that singing in a choir (active music) yielded a greater improvement in performance compared to passive listening for brief time periods.

Here, the authors sought to better understand how and why people experience beauty in music. They explored this fundamental aesthetic response by considering numerous emotional responses of participants to diverse musical excerpts using a 42-item Aesthetic Emotions Scale assessment. They found that the highly nuanced emotional experience of beauty in music includes positive, negative, and knowledge-related feelings.

Herring and Scott investigated how specific types of background music affected 8th and 9th graders' performance on a reading comprehension task. In the study, their results indicated that music with English lyrics led to lower reading comprehension scores, while foreign language and instrumental music was comparable to no music at all. The authors therefore recommend that teachers avoid playing English language music for students completing reading tasks in order to minimize distractions and improve work efficiency.

Recurrent neural networks (RNNs) are useful for text generation since they can generate outputs in the context of previous ones. Baroque music and language are similar, as every word or note exists in context with others, and they both follow strict rules. The authors hypothesized that if we represent music in a text format, an RNN designed to generate language could train on it and create music structurally similar to Bach’s. They found that the music generated by our RNN shared a similar structure with Bach’s music in the input dataset, while Bachbot’s outputs are significantly different from this experiment’s outputs and thus are less similar to Bach’s repertoire compared to our algorithm.

Jazz music is a unique American art form that has spread around the world. Iyer and Iyer study this spread through a computational sociology project examining how jazz popularity is correlated with postmaterialism (an ideology that values self-expression) and political activity.

Vibrato, defined as a rapid and subtle oscillation in pitch, is a technique that is commonly used by musicians to add expression and colour to notes. However, on stringed instruments, there are certain notes (open string notes) on which it is impossible to perform the technique. Without vibrato, they can sound angular and unpleasant, especially when juxtaposed against other notes played with vibrato. String players therefore use an alternative to achieve the same vibrato effect on the open string — a technique referred to as “open string vibrato”. While the technique is widely used, it is unknown how much of a physical effect it has on the sound waves produced, if any at all. The purpose of this study is to analyse open string vibrato using a statistical approach to provide evidence to characterize the physical effect of the technique, and then compare it to normal vibrato. We hypothesised that it would have a noticeable and measurable effect on the sound waves produced because of the technique’s widespread usage. To test this, notes, with and without either open string vibrato or normal vibrato, were recorded on the violin. We analyzed the audio recordings using a computational and statistical approach. The results of the study partially agreed with our hypothesis: while the technique has an observable physical effect on the sound waves, the effect is weaker than expected. We concluded that open string vibrato does work, but has quite a subtle effect, and thus should only be used when there is no other option.

Here, the authors investigated the effects of an interventional psychology on the study habits of high school students specifically related to the use of electronic distractions such as social media or texting, listening to music, or watching TV. They reported varying degrees of success between the control and intervention groups, suggesting that the methods of habit-breaking for students merits further study.

In this study the authors looked at the ability of artificial intelligence to detect tempo, rhythm, and intonation of a piece played on violin. Technology such as this would allow for students to practice and get feedback without the need of a teacher.

Ashley Moulton & Joseph Rasmus investigate 9 controversial categories of intelligence as predicted by Multiple Intelligence Theory, originally proposed in the mid-1980s. By collecting data from 56 participants, they record that there may not actually be a correlation between these categorical types when it comes to workplace atmosphere and project efficiency.