Music INTerval Back prOPagation (MINTBOP)
There is no back propagation involved with this app(it just works with the name). The aim of this app is to help you develop musical interval identification by getting you to recognise the melody you've decided to associate with a given interval. In theory, the better you get at recognising the melody, the earlier you will recognise it, until eventually you can recognise the tune just by hearing the first interval.
For every interval (minor 2nd to octave (ascending and descending)) you can program the tune to associate with it. Then, when you hit play at the bottom of the main screen, the app will keep picking tunes from that list randomly. The idea is that you will be able to practise recognising the melody you have programmed in to the point of recognising the melody just by the first interval, at which point you can identify the melodic intervals.
The advantage of practice like this is that you can capitalise on an already existing ability to recognise a tune. As melodies can be expected to be more than two notes long, there is more information available than just the two notes of an interval to identify the melody(and thereby the interval). This fixes a problem that probably most people feel familiar with that have tried to learn to identify music intervals, which is that you can replay an interval many times and still struggle to identify it even after you know what the interval is. Essentially, the feedback is too slow and not easy to assimilate.
The extra information related to the interval(i.e. the other music notes) being released gradually(i.e. note by note) causes you to practise the task of categorising the initial interval and having it match the feedback that is rest of the melody. This 'feedback' does not require much conscious effort or concentration to receive. It is quite easy to recognise music once it gets going and so the feedback is also very clear as well as fast.
If you struggle to recognise the melody within the first interval and maybe only recognise the melody after five notes are played, then listening to the random melodies will naturally cause you to try to recognise the interval within four notes(with feedback being the fifth note). If you struggle instead to recognise the melody before four notes are played, then you will end up trying to recognise it within three notes(with the feedback being the fourth note). As you can see, the rate of feedback automatically adapts to your ability.
So with responsive, clear, and adaptable feedback, hopefully the app will make learning how to identify melodic intervals a bit less boring and difficult. Interestingly enough, these are necessary characteristics of learning environments for inducing the flow state and also for optimal neural network learning(that's what I've heard at least). It turns out(according to the internet) that back propagation in neural networks is especially efficient under these conditions of feedback. So 'back propagation' was justified in the name of the app after all(or at least, kind of justified).
There is no back propagation involved with this app(it just works with the name). The aim of this app is to help you develop musical interval identification by getting you to recognise the melody you've decided to associate with a given interval. In theory, the better you get at recognising the melody, the earlier you will recognise it, until eventually you can recognise the tune just by hearing the first interval.
For every interval (minor 2nd to octave (ascending and descending)) you can program the tune to associate with it. Then, when you hit play at the bottom of the main screen, the app will keep picking tunes from that list randomly. The idea is that you will be able to practise recognising the melody you have programmed in to the point of recognising the melody just by the first interval, at which point you can identify the melodic intervals.
The advantage of practice like this is that you can capitalise on an already existing ability to recognise a tune. As melodies can be expected to be more than two notes long, there is more information available than just the two notes of an interval to identify the melody(and thereby the interval). This fixes a problem that probably most people feel familiar with that have tried to learn to identify music intervals, which is that you can replay an interval many times and still struggle to identify it even after you know what the interval is. Essentially, the feedback is too slow and not easy to assimilate.
The extra information related to the interval(i.e. the other music notes) being released gradually(i.e. note by note) causes you to practise the task of categorising the initial interval and having it match the feedback that is rest of the melody. This 'feedback' does not require much conscious effort or concentration to receive. It is quite easy to recognise music once it gets going and so the feedback is also very clear as well as fast.
If you struggle to recognise the melody within the first interval and maybe only recognise the melody after five notes are played, then listening to the random melodies will naturally cause you to try to recognise the interval within four notes(with feedback being the fifth note). If you struggle instead to recognise the melody before four notes are played, then you will end up trying to recognise it within three notes(with the feedback being the fourth note). As you can see, the rate of feedback automatically adapts to your ability.
So with responsive, clear, and adaptable feedback, hopefully the app will make learning how to identify melodic intervals a bit less boring and difficult. Interestingly enough, these are necessary characteristics of learning environments for inducing the flow state and also for optimal neural network learning(that's what I've heard at least). It turns out(according to the internet) that back propagation in neural networks is especially efficient under these conditions of feedback. So 'back propagation' was justified in the name of the app after all(or at least, kind of justified).
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