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Hittade 3 uppsatser som matchar ovanstående sökkriterier.

  1. 1. Expressive Automatic Music Transcription : Using hard onset detection to transcribe legato slurs for violin

    Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Författare :Simon Falk; [2022]
    Nyckelord :Automatic Music Transcription; Signal Processing; Convolutional Neural Networks; Onset Detection; Music Information Retrieval; Automatisk musiktranskription; Signalbearbetning; Faltningsnätverk; Ansatsdetektion; Informationssökning av musik;

    Sammanfattning : Automatic Music Transcriptions systems such as ScoreCloud aims to convert audio signals to sheet music. The information contained in sheet music can be divided into increasingly descriptive layers, where most research on Automatic Music Transcription is restricted on note-level transcription and disregard expressive markings such as legato slurs. LÄS MER

  3. 2. Reproducing the state of the art in onset detection using neural networks

    Kandidat-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Författare :Björn Lindqvist; [2019]
    Nyckelord :;

    Sammanfattning : Great strides have been made in the state of the art performance of musicial onset detection in recent years with better and better detectors being invented at a fast pace. The current top spot is held by Schlüter and Böck, who in 2014 presented a detector based on a convolutional neural network (CNN) that attained an F-score of 90. LÄS MER

  4. 3. Onset detection in polyphonic music

    Master-uppsats, KTH/Tal, musik och hörsel, TMH

    Författare :Nils Efraimsson; [2017]
    Nyckelord :Acoustics; onset detection; Musikakustik; ansatsdetektion;

    Sammanfattning : In music analysis, the beginning of events in a music signal (i.e. sound onset detection) is important for such tasks as sound segmentation, beat recognition and automatic music transcription. The aim of the present work was to make an algorithm for sound onset detection with better performance than other state-of-the-art1 algorithms. LÄS MER