Matrix profile VI: Meaningful multidimensional motif discovery
Time series motifs are approximately repeating patterns in real-valued time series data.
They are useful for exploratory data mining and are often used as inputs for various time …
They are useful for exploratory data mining and are often used as inputs for various time …
Rolling bearing fault severity recognition via data mining integrated with convolutional neural network
D Liu, L Cui, W Cheng, D Zhao, W Wen - IEEE Sensors Journal, 2022 - ieeexplore.ieee.org
Rolling bearing vibration signals exhibit typically complex modulation characteristics, and
usually present nonstationary features. The defect of a rolling bearing is mainly manifested …
usually present nonstationary features. The defect of a rolling bearing is mainly manifested …
Matrix profile XIV: scaling time series motif discovery with GPUs to break a quintillion pairwise comparisons a day and beyond
The discovery of conserved (repeated) patterns in time series is arguably the most important
primitive in time series data mining. Called time series motifs, these primitive patterns are …
primitive in time series data mining. Called time series motifs, these primitive patterns are …
Generative autoregressive networks for 3d dancing move synthesis from music
This letter proposes a framework which is able to generate a sequence of three-dimensional
human dance poses for a given music. The proposed framework consists of three …
human dance poses for a given music. The proposed framework consists of three …
Accurate and scalable version identification using musically-motivated embeddings
The version identification (VI) task deals with the automatic detection of recordings that
correspond to the same underlying musical piece. Despite many efforts, VI is still an open …
correspond to the same underlying musical piece. Despite many efforts, VI is still an open …
Bytecover: Cover song identification via multi-loss training
We present in this paper ByteCover, which is a new feature learning method for cover song
identification (CSI). Byte-Cover is built based on the classical ResNet model, and two major …
identification (CSI). Byte-Cover is built based on the classical ResNet model, and two major …
Fast similarity matrix profile for music analysis and exploration
Most algorithms for music data mining and retrieval analyze the similarity between feature
sets extracted from the raw audio. A conventional approach to assess similarities within or …
sets extracted from the raw audio. A conventional approach to assess similarities within or …
Inpainting of long audio segments with similarity graphs
We present a novel method for the compensation of long duration data loss in audio signals,
in particular music. The concealment of such signal defects is based on a graph that …
in particular music. The concealment of such signal defects is based on a graph that …
Key-invariant convolutional neural network toward efficient cover song identification
X Xu, X Chen, D Yang - 2018 IEEE International Conference on …, 2018 - ieeexplore.ieee.org
Cover song identification has long been a challenging task due to key, timbre and structure
variations in different renditions of a song. Previous research mostly involves handcrafted …
variations in different renditions of a song. Previous research mostly involves handcrafted …
Learning a representation for cover song identification using convolutional neural network
Cover song identification is a challenging task in the field of Music Information Retrieval
(MIR) due to complex musical variations between query tracks and cover versions. Previous …
(MIR) due to complex musical variations between query tracks and cover versions. Previous …