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Music Signal Processing

DRUM TRANSCRIPTION FROM POLYPHONIC MUSIC WITH RECURRENT NEURAL NETWORKS


Automatic drum transcription methods aim at extracting a symbolic representation of notes played by a drum kit in audio recordings. For automatic music analysis, this task is of particular interest as such a transcript can be used to extract high level information about the piece, e.g., tempo, downbeat positions, meter, and genre cues. In this work, an approach to transcribe drums from polyphonic audio signals based on a re- current neural network is presented. Deep learning techniques like dropout and data augmentation are applied to improve the generalization capabilities of the system.

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Authors:
Richard Vogl, Matthias Dorfer, Peter Knees
Submitted On:
9 March 2017 - 6:57pm
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drum-transcription_icassp_4_3.pdf

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[1] Richard Vogl, Matthias Dorfer, Peter Knees, "DRUM TRANSCRIPTION FROM POLYPHONIC MUSIC WITH RECURRENT NEURAL NETWORKS", IEEE SigPort, 2017. [Online]. Available: http://sigport.org/1732. Accessed: Apr. 24, 2017.
@article{1732-17,
url = {http://sigport.org/1732},
author = {Richard Vogl; Matthias Dorfer; Peter Knees },
publisher = {IEEE SigPort},
title = {DRUM TRANSCRIPTION FROM POLYPHONIC MUSIC WITH RECURRENT NEURAL NETWORKS},
year = {2017} }
TY - EJOUR
T1 - DRUM TRANSCRIPTION FROM POLYPHONIC MUSIC WITH RECURRENT NEURAL NETWORKS
AU - Richard Vogl; Matthias Dorfer; Peter Knees
PY - 2017
PB - IEEE SigPort
UR - http://sigport.org/1732
ER -
Richard Vogl, Matthias Dorfer, Peter Knees. (2017). DRUM TRANSCRIPTION FROM POLYPHONIC MUSIC WITH RECURRENT NEURAL NETWORKS. IEEE SigPort. http://sigport.org/1732
Richard Vogl, Matthias Dorfer, Peter Knees, 2017. DRUM TRANSCRIPTION FROM POLYPHONIC MUSIC WITH RECURRENT NEURAL NETWORKS. Available at: http://sigport.org/1732.
Richard Vogl, Matthias Dorfer, Peter Knees. (2017). "DRUM TRANSCRIPTION FROM POLYPHONIC MUSIC WITH RECURRENT NEURAL NETWORKS." Web.
1. Richard Vogl, Matthias Dorfer, Peter Knees. DRUM TRANSCRIPTION FROM POLYPHONIC MUSIC WITH RECURRENT NEURAL NETWORKS [Internet]. IEEE SigPort; 2017. Available from : http://sigport.org/1732

Polyphonic Piano Note Transcription with Non-negative Matrix Factorization of Differential Spectrogram

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Authors:
Li Su, YI-HSUAN YANG, TAN LEE
Submitted On:
11 March 2017 - 8:48pm
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icassp2017_sf.pdf

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[1] Li Su, YI-HSUAN YANG, TAN LEE, "Polyphonic Piano Note Transcription with Non-negative Matrix Factorization of Differential Spectrogram", IEEE SigPort, 2017. [Online]. Available: http://sigport.org/1573. Accessed: Apr. 24, 2017.
@article{1573-17,
url = {http://sigport.org/1573},
author = {Li Su; YI-HSUAN YANG; TAN LEE },
publisher = {IEEE SigPort},
title = {Polyphonic Piano Note Transcription with Non-negative Matrix Factorization of Differential Spectrogram},
year = {2017} }
TY - EJOUR
T1 - Polyphonic Piano Note Transcription with Non-negative Matrix Factorization of Differential Spectrogram
AU - Li Su; YI-HSUAN YANG; TAN LEE
PY - 2017
PB - IEEE SigPort
UR - http://sigport.org/1573
ER -
Li Su, YI-HSUAN YANG, TAN LEE. (2017). Polyphonic Piano Note Transcription with Non-negative Matrix Factorization of Differential Spectrogram. IEEE SigPort. http://sigport.org/1573
Li Su, YI-HSUAN YANG, TAN LEE, 2017. Polyphonic Piano Note Transcription with Non-negative Matrix Factorization of Differential Spectrogram. Available at: http://sigport.org/1573.
Li Su, YI-HSUAN YANG, TAN LEE. (2017). "Polyphonic Piano Note Transcription with Non-negative Matrix Factorization of Differential Spectrogram." Web.
1. Li Su, YI-HSUAN YANG, TAN LEE. Polyphonic Piano Note Transcription with Non-negative Matrix Factorization of Differential Spectrogram [Internet]. IEEE SigPort; 2017. Available from : http://sigport.org/1573

DETECTION OF IMPULSIVE DISTURBANCES IN ARCHIVE AUDIO SIGNALS


The problem of detection of impulsive disturbances in archive audio signals is considered. It is shown that semi-causal/noncausal solutions based on joint evaluation of signal prediction errors and leave-one-out signal interpolation errors, allow one to noticeably improve detection results compared to the prediction-only based solutions. The proposed approaches are evaluated on a set of clean audio signals contaminated with real click waveforms extracted from silent parts of old gramophone recordings.

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Authors:
Marcin Ciołek, Niedźwiecki Maciej
Submitted On:
27 February 2017 - 3:05pm
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Poster ICASSP 2017

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[1] Marcin Ciołek, Niedźwiecki Maciej , "DETECTION OF IMPULSIVE DISTURBANCES IN ARCHIVE AUDIO SIGNALS", IEEE SigPort, 2017. [Online]. Available: http://sigport.org/1447. Accessed: Apr. 24, 2017.
@article{1447-17,
url = {http://sigport.org/1447},
author = {Marcin Ciołek; Niedźwiecki Maciej },
publisher = {IEEE SigPort},
title = {DETECTION OF IMPULSIVE DISTURBANCES IN ARCHIVE AUDIO SIGNALS},
year = {2017} }
TY - EJOUR
T1 - DETECTION OF IMPULSIVE DISTURBANCES IN ARCHIVE AUDIO SIGNALS
AU - Marcin Ciołek; Niedźwiecki Maciej
PY - 2017
PB - IEEE SigPort
UR - http://sigport.org/1447
ER -
Marcin Ciołek, Niedźwiecki Maciej . (2017). DETECTION OF IMPULSIVE DISTURBANCES IN ARCHIVE AUDIO SIGNALS. IEEE SigPort. http://sigport.org/1447
Marcin Ciołek, Niedźwiecki Maciej , 2017. DETECTION OF IMPULSIVE DISTURBANCES IN ARCHIVE AUDIO SIGNALS. Available at: http://sigport.org/1447.
Marcin Ciołek, Niedźwiecki Maciej . (2017). "DETECTION OF IMPULSIVE DISTURBANCES IN ARCHIVE AUDIO SIGNALS." Web.
1. Marcin Ciołek, Niedźwiecki Maciej . DETECTION OF IMPULSIVE DISTURBANCES IN ARCHIVE AUDIO SIGNALS [Internet]. IEEE SigPort; 2017. Available from : http://sigport.org/1447

The Singing Voice Before and After Vocal Warm-up by Students of Chinese National Singing


This paper compared the singing voices of four student singers of Chinese national singing before and after vocal warm-up. Statistics showed that the parameters such as deviation from the standard note, vibrato rate and jitter were undergoing significant changes after 30 minutes of warming up exercise, while the differences of vibrato extent demonstrated a controversy result.

Paper Details

Authors:
Weifeng Kong, Yujie Chi, Yanting Chen, Jianguo Wei, Jianwu Dang
Submitted On:
16 October 2016 - 11:53pm
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SingVoice_poster_6.pdf

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[1] Weifeng Kong, Yujie Chi, Yanting Chen, Jianguo Wei, Jianwu Dang, "The Singing Voice Before and After Vocal Warm-up by Students of Chinese National Singing", IEEE SigPort, 2016. [Online]. Available: http://sigport.org/1257. Accessed: Apr. 24, 2017.
@article{1257-16,
url = {http://sigport.org/1257},
author = {Weifeng Kong; Yujie Chi; Yanting Chen; Jianguo Wei; Jianwu Dang },
publisher = {IEEE SigPort},
title = {The Singing Voice Before and After Vocal Warm-up by Students of Chinese National Singing},
year = {2016} }
TY - EJOUR
T1 - The Singing Voice Before and After Vocal Warm-up by Students of Chinese National Singing
AU - Weifeng Kong; Yujie Chi; Yanting Chen; Jianguo Wei; Jianwu Dang
PY - 2016
PB - IEEE SigPort
UR - http://sigport.org/1257
ER -
Weifeng Kong, Yujie Chi, Yanting Chen, Jianguo Wei, Jianwu Dang. (2016). The Singing Voice Before and After Vocal Warm-up by Students of Chinese National Singing. IEEE SigPort. http://sigport.org/1257
Weifeng Kong, Yujie Chi, Yanting Chen, Jianguo Wei, Jianwu Dang, 2016. The Singing Voice Before and After Vocal Warm-up by Students of Chinese National Singing. Available at: http://sigport.org/1257.
Weifeng Kong, Yujie Chi, Yanting Chen, Jianguo Wei, Jianwu Dang. (2016). "The Singing Voice Before and After Vocal Warm-up by Students of Chinese National Singing." Web.
1. Weifeng Kong, Yujie Chi, Yanting Chen, Jianguo Wei, Jianwu Dang. The Singing Voice Before and After Vocal Warm-up by Students of Chinese National Singing [Internet]. IEEE SigPort; 2016. Available from : http://sigport.org/1257

The Singing Voice Before and After Vocal Warm-up by Students of Chinese National Singing


This paper compared the singing voices of four student singers of Chinese national singing before and after vocal warm-up. Statistics showed that the parameters such as deviation from the standard note, vibrato rate and jitter were undergoing significant changes after 30 minutes of warming up exercise, while the differences of vibrato extent demonstrated a controversy result.

Paper Details

Authors:
Yu Chen, Weifeng Kong, Yujie Chi, Yanting Chen, Jianguo Wei, Jianwu Dang
Submitted On:
16 October 2016 - 11:53pm
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Document Files

SingVoice_poster_6.pdf

(95 downloads)

Keywords

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[1] Yu Chen, Weifeng Kong, Yujie Chi, Yanting Chen, Jianguo Wei, Jianwu Dang, "The Singing Voice Before and After Vocal Warm-up by Students of Chinese National Singing", IEEE SigPort, 2016. [Online]. Available: http://sigport.org/1256. Accessed: Apr. 24, 2017.
@article{1256-16,
url = {http://sigport.org/1256},
author = {Yu Chen; Weifeng Kong; Yujie Chi; Yanting Chen; Jianguo Wei; Jianwu Dang },
publisher = {IEEE SigPort},
title = {The Singing Voice Before and After Vocal Warm-up by Students of Chinese National Singing},
year = {2016} }
TY - EJOUR
T1 - The Singing Voice Before and After Vocal Warm-up by Students of Chinese National Singing
AU - Yu Chen; Weifeng Kong; Yujie Chi; Yanting Chen; Jianguo Wei; Jianwu Dang
PY - 2016
PB - IEEE SigPort
UR - http://sigport.org/1256
ER -
Yu Chen, Weifeng Kong, Yujie Chi, Yanting Chen, Jianguo Wei, Jianwu Dang. (2016). The Singing Voice Before and After Vocal Warm-up by Students of Chinese National Singing. IEEE SigPort. http://sigport.org/1256
Yu Chen, Weifeng Kong, Yujie Chi, Yanting Chen, Jianguo Wei, Jianwu Dang, 2016. The Singing Voice Before and After Vocal Warm-up by Students of Chinese National Singing. Available at: http://sigport.org/1256.
Yu Chen, Weifeng Kong, Yujie Chi, Yanting Chen, Jianguo Wei, Jianwu Dang. (2016). "The Singing Voice Before and After Vocal Warm-up by Students of Chinese National Singing." Web.
1. Yu Chen, Weifeng Kong, Yujie Chi, Yanting Chen, Jianguo Wei, Jianwu Dang. The Singing Voice Before and After Vocal Warm-up by Students of Chinese National Singing [Internet]. IEEE SigPort; 2016. Available from : http://sigport.org/1256

Automatic Lyrics Display System for Live Music Performances


Live musical performances (e.g., choruses, concerts, and operas) often require the display of lyrics for the convenience of the audience. This requires following the performance and controlling the lyrics display in real time. In practice, this is usually controlled by a staff member of the concert who has been very familiar with the performance. In this paper, we present our effort in implementing a computational system to automate this real-time lyric display process using music following techniques.

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Authors:
Karan Vombatkere, Bochen Li
Submitted On:
31 July 2016 - 3:58pm
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VombatkereLi_AutomaticLyricsDisplaySystem_IEEESPM16_Final.pdf

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[1] Karan Vombatkere, Bochen Li, "Automatic Lyrics Display System for Live Music Performances", IEEE SigPort, 2016. [Online]. Available: http://sigport.org/1141. Accessed: Apr. 24, 2017.
@article{1141-16,
url = {http://sigport.org/1141},
author = {Karan Vombatkere; Bochen Li },
publisher = {IEEE SigPort},
title = {Automatic Lyrics Display System for Live Music Performances},
year = {2016} }
TY - EJOUR
T1 - Automatic Lyrics Display System for Live Music Performances
AU - Karan Vombatkere; Bochen Li
PY - 2016
PB - IEEE SigPort
UR - http://sigport.org/1141
ER -
Karan Vombatkere, Bochen Li. (2016). Automatic Lyrics Display System for Live Music Performances. IEEE SigPort. http://sigport.org/1141
Karan Vombatkere, Bochen Li, 2016. Automatic Lyrics Display System for Live Music Performances. Available at: http://sigport.org/1141.
Karan Vombatkere, Bochen Li. (2016). "Automatic Lyrics Display System for Live Music Performances." Web.
1. Karan Vombatkere, Bochen Li. Automatic Lyrics Display System for Live Music Performances [Internet]. IEEE SigPort; 2016. Available from : http://sigport.org/1141

Automatic Chord Estimation on SeventhsBass Chord Vocabulary Using Deep Neural Network

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Authors:
Junqi Deng, Yu-Kwong Kwok
Submitted On:
20 March 2016 - 10:18pm
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ICASSP2016.pdf

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[1] Junqi Deng, Yu-Kwong Kwok, "Automatic Chord Estimation on SeventhsBass Chord Vocabulary Using Deep Neural Network", IEEE SigPort, 2016. [Online]. Available: http://sigport.org/902. Accessed: Apr. 24, 2017.
@article{902-16,
url = {http://sigport.org/902},
author = {Junqi Deng; Yu-Kwong Kwok },
publisher = {IEEE SigPort},
title = {Automatic Chord Estimation on SeventhsBass Chord Vocabulary Using Deep Neural Network},
year = {2016} }
TY - EJOUR
T1 - Automatic Chord Estimation on SeventhsBass Chord Vocabulary Using Deep Neural Network
AU - Junqi Deng; Yu-Kwong Kwok
PY - 2016
PB - IEEE SigPort
UR - http://sigport.org/902
ER -
Junqi Deng, Yu-Kwong Kwok. (2016). Automatic Chord Estimation on SeventhsBass Chord Vocabulary Using Deep Neural Network. IEEE SigPort. http://sigport.org/902
Junqi Deng, Yu-Kwong Kwok, 2016. Automatic Chord Estimation on SeventhsBass Chord Vocabulary Using Deep Neural Network. Available at: http://sigport.org/902.
Junqi Deng, Yu-Kwong Kwok. (2016). "Automatic Chord Estimation on SeventhsBass Chord Vocabulary Using Deep Neural Network." Web.
1. Junqi Deng, Yu-Kwong Kwok. Automatic Chord Estimation on SeventhsBass Chord Vocabulary Using Deep Neural Network [Internet]. IEEE SigPort; 2016. Available from : http://sigport.org/902