Automatic music transcription: challenges and future directions
Automatic music transcription is considered by many to be a key enabling technology in
music signal processing. However, the performance of transcription systems is still …
music signal processing. However, the performance of transcription systems is still …
Online human action detection using joint classification-regression recurrent neural networks
Human action recognition from well-segmented 3D skeleton data has been intensively
studied and has been attracting an increasing attention. Online action detection goes one …
studied and has been attracting an increasing attention. Online action detection goes one …
Improved musical onset detection with convolutional neural networks
J Schlüter, S Böck - 2014 ieee international conference on …, 2014 - ieeexplore.ieee.org
Musical onset detection is one of the most elementary tasks in music analysis, but still only
solved imperfectly for polyphonic music signals. Interpreted as a computer vision problem in …
solved imperfectly for polyphonic music signals. Interpreted as a computer vision problem in …
Music2dance: Dancenet for music-driven dance generation
Synthesize human motions from music (ie, music to dance) is appealing and has attracted
lots of research interests in recent years. It is challenging because of the requirement for …
lots of research interests in recent years. It is challenging because of the requirement for …
[PDF][PDF] Maximum filter vibrato suppression for onset detection
We present SuperFlux-a new onset detection algorithm with vibrato suppression. It is an
enhanced version of the universal spectral flux onset detection algorithm, and reduces the …
enhanced version of the universal spectral flux onset detection algorithm, and reduces the …
[PDF][PDF] Evaluating the Online Capabilities of Onset Detection Methods.
In this paper, we evaluate various onset detection algorithms in terms of their online
capabilities. Most methods use some kind of normalization over time, which renders them …
capabilities. Most methods use some kind of normalization over time, which renders them …
[PDF][PDF] Automatic Drum Transcription using Bi-directional Recurrent Neural Networks.
Automatic drum transcription (ADT) systems attempt to generate a symbolic music notation
for percussive instruments in audio recordings. Neural networks have already been shown …
for percussive instruments in audio recordings. Neural networks have already been shown …
[PDF][PDF] Musical onset detection with convolutional neural networks
J Schlüter, S Böck - 6th international workshop on machine learning and …, 2013 - ofai.at
Detecting musical onsets is the first step for many aspects of music analysis, but still lacks
accuracy for polyphonic music signals. We perform an initial exploration of the effectiveness …
accuracy for polyphonic music signals. We perform an initial exploration of the effectiveness …
A comparison of deep learning inference engines for embedded real-time audio classification
Recent advancements in deep learning have shown great potential for audio applications,
improving the accuracy of previous solutions for tasks such as music transcription, beat …
improving the accuracy of previous solutions for tasks such as music transcription, beat …
[PDF][PDF] Hierarchical Classification Networks for Singing Voice Segmentation and Transcription.
Identifying the onset and offset time of a note is a challenging step in singing voice
transcription, as the soft onset/offset, portamento, and vibrato phenomena are rich in singing …
transcription, as the soft onset/offset, portamento, and vibrato phenomena are rich in singing …