We call this a supervised approach, as it requires a training stage before the method can be used to perform a transcription. We use individually recorded notes from a piano as atoms, and CSC tries to reconstruct the performance by identifying the notes that have been played and by patching the corresponding atoms together at the right time. CSC aims to reconstruct a signal (a digitized image or a digital music recording) by combining small elements called atoms. Our approach is based on a technique called Convolutional Sparse Coding (CSC), which has been successfully applied to several computer vision problems. An AMT system could be used to record and transcribe a piece performed by a student, and a separate component could be used to compare the performance with the original score, highlighting the performance errors. Beginner piano students need constant supervision during their practice, as they might not be able to recognize errors while they practice a new piece, yet having constant supervision by a music teacher is impractical and too expensive. AMT systems could also be incorporated in more complex programs to help piano students during their practice. AMT has several applications in music education, such as helping music students in self checking their auditory skills, or helping amateur musicians by generating music scores that would be impossible to obtain otherwise. Even the best algorithms cannot match human performance, and the transcribed pieces normally contain a large number of errors, in the form of wrong notes or missing notes. However, the results are still behind the capabilities of a trained musician and unsatisfactory for practical purposes.

Why is it important?ĪMT is a fundamental problem in Computer Audition and Music Information Retrieval and has been studied for several decades. Automatic Music Transcription (AMT) aims at automating this process by using computers and computer programs, so instead of transcribing the piece manually, you just feed the audio to a computer, and the computer generates the music score for you. Musicians spend a considerable amount of time training their ears and their transcription skills, but the transcription process is usually quite time consuming. Then you have to patiently listen to the piece over and over, while writing down all the notes. Imagine you are a pianist and you hear a nice piece that you would like to play, but the score is not available, which is typical for certain music genres like jazz improvisations. Music Transcription is the process of notating a music piece solely by listening.

Piano transcriptions software