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Rewind: A Music Transcription Method
AuthorCarthen, Chase Dwayne
Computer Science and Engineering
StatisticsView Usage Statistics
Music is commonly recorded, played, and shared through digital audio formatssuch as wav, mp3, and various others. These formats are easy to use, but they lackthe symbolic information that musicians, bands, and other artists need to retrieveimportant information out of a given piece. There have been recent advances in theMusic Information Retrieval (MIR) field for converting from a digital audio format toa symbolic format. This problem is called Music Transcription and the systems builtto solve this problem are called Automatic Music Transcription (AMT) systems. Therecent advances in the MIR field have yielded more accurate algorithms using differenttypes of neural networks from deep learning and iterative approaches. Rewind’sapproach is similar but boasts a new method using an encoder-decoder network wherethe encoder and decoder both consist of a gated recurrent unit and a linear layer.The encoder layer of Rewind is a single layer autoencoder that captures the temporaldependencies of a song and produces a temporal encoding. In other words, Rewindis a web app that utilizes a deep learning method to allow users to transcribe, listento, and see their music.