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Audio-Visual Scene Understanding

Di Hu
2021 Zenodo  
• Challenges -Polyphonic -Rich timbre -Music language model -Lack of annotated data Piano Transcription • Disklavier piano: acoustic piano that records MIDI and can reproduce audio from MIDI  ...  maybe overlapped by noise or other sources  Rich semantic meaning  Often with reverberation  Sporadic but can be polyphonic  Long-tail distribution  Wide range of duration  Less structured  ... 
doi:10.5281/zenodo.5013725 fatcat:zzkh6dxfjzdd7apq46jsx3qvve

An Rnn-Based Music Language Model For Improving Automatic Music Transcription

Siddharth Sigtia, Emmanouil Benetos, Srikanth Cherla, Tillman Weyde, Artur S. D'Avila Garcez, Simon Dixon
2014 Zenodo  
The model performed classification using support vector machines and was applied to piano music.  ...  Böck and Schedl used recurrent neural networks (RNNs) with Long Short-Term Memory units for performing polyphonic piano transcription [8] , with the system being particularly good at recognising note  ... 
doi:10.5281/zenodo.1416792 fatcat:rsz2b3qh7jh3pes2pziziwtb6m

Survey on automatic transcription of music

Tiago Fernandes Tavares, Jayme Garcia Arnal Barbedo, Romis Attux, Amauri Lopes
2013 Journal of the Brazilian Computer Society  
Many techniques have been proposed to solve the problem of automatic music transcription.  ...  This paper presents an overview on the theme, discussing digital signal processing techniques, pattern classification techniques and heuristic assumptions derived from music knowledge that were used to  ...  Guibin Z, Sheng L (2007) Automatic transcription method for polyphonic music based on adaptive comb filter and neural network.  ... 
doi:10.1007/s13173-013-0118-6 fatcat:pn2meihauvhfha6usww6dpbyu4

Modeling Temporal Dependencies in High-Dimensional Sequences: Application to Polyphonic Music Generation and Transcription [article]

Nicolas Boulanger-Lewandowski, Yoshua Bengio
2012 arXiv   pre-print
We investigate the problem of modeling symbolic sequences of polyphonic music in a completely general piano-roll representation.  ...  We show how our musical language model can serve as a symbolic prior to improve the accuracy of polyphonic transcription.  ...  Conclusions We presented an RNN-based model that can learn harmonic and rhythmic probabilistic rules from polyphonic music scores of varying complexity, substantially better than popular methods in music  ... 
arXiv:1206.6392v1 fatcat:64ynoazx2baofbjig6qm33qsze

Polyphonic piano note transcription with recurrent neural networks

Sebastian Bock, Markus Schedl
2012 2012 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)  
In this paper a new approach for polyphonic piano note onset transcription is presented.  ...  Long Short-Term Memory units are used in a bidirectional neural network to model the context of the notes.  ...  Traditional music transcription systems are based on a wide range of different technologies, but all have to deal with the subtasks of estimating the fundamental frequencies and the onset locations of  ... 
doi:10.1109/icassp.2012.6287832 dblp:conf/icassp/BockS12 fatcat:3suzzh7uojbt7abftittlcasdy

Multi-instrument music transcription based on deep spherical clustering of spectrograms and pitchgrams

Keitaro Tanaka, Takayuki Nakatsuka, Ryo Nishikimi, Kazuyoshi Yoshii, Shigeo Morishima
2020 Zenodo  
This paper describes a clustering-based music transcription method that estimates the piano rolls of arbitrary musical instrument parts from multi-instrument polyphonic music signals.  ...  If target musical pieces are always played by particular kinds of musical instruments, a way to obtain piano rolls is to compute the pitchgram (pitch saliency spectrogram) of each musical instrument by  ...  In this paper, we propose a new method to estimate the piano rolls of arbitrary musical instrument parts from multi-instrument polyphonic music signals based on deep clustering ( Figure 1 ).  ... 
doi:10.5281/zenodo.4245435 fatcat:ziaurfyjpfbx5fokuk3euooctm

Automatic Lyrics Alignment and Transcription in Polyphonic Music: Does Background Music Help? [article]

Chitralekha Gupta, Emre Yılmaz, Haizhou Li
2019 arXiv   pre-print
Automatic lyrics alignment and transcription in polyphonic music are challenging tasks because the singing vocals are corrupted by the background music.  ...  We then present the lyrics alignment and transcription performance of music-informed acoustic models for the best-performing pipeline, and systematically study the impact of music genre and language model  ...  [7] adopted an automatic speech recognition (ASR) based approach for phoneme and word recognition of singing vocals in monophonic and polyphonic music.  ... 
arXiv:1909.10200v2 fatcat:6sc6dywp6jcvzhf35pyyluly3a

A Holistic Approach to Polyphonic Music Transcription with Neural Networks

Miguel Roman, Antonio Pertusa, Jorge Calvo-Zaragoza
2019 Zenodo  
Most previous Automatic Music Transcription (AMT) methods seek a piano-roll representation of the pitches, that can be further transformed into a score by incorporating tempo estimation, beat tracking,  ...  We present a framework based on neural networks to extract music scores directly from polyphonic audio in an end-to-end fashion.  ...  Note-level transcription goes a step further by estimating the notes characterized by their pitch and clock-time duration (onset and offset times), producing a piano-roll representation of the music.  ... 
doi:10.5281/zenodo.3527914 fatcat:otrre7szwnfl7hifsbdee25ree

An End-to-End Neural Network for Polyphonic Piano Music Transcription [article]

Siddharth Sigtia, Emmanouil Benetos, Simon Dixon
2016 arXiv   pre-print
We present a supervised neural network model for polyphonic piano music transcription.  ...  We compare performance of the neural network based acoustic models with two popular unsupervised acoustic models.  ...  Abstract-We present a supervised neural network model for polyphonic piano music transcription.  ... 
arXiv:1508.01774v2 fatcat:ktwpjxr3n5b2tjov55efittsei

Polyphonic Music Modelling with LSTM-RTRBM

Qi Lyu, Zhiyong Wu, Jun Zhu
2015 Proceedings of the 23rd ACM international conference on Multimedia - MM '15  
In this paper, we present LSTM-RTRBM, a new neural network model for the problem of creating accurate yet flexible models of polyphonic music.  ...  Our approach greatly improves the performance of polyphonic music sequence modelling, achieving the state-of-the-art results on multiple datasets.  ...  transcription of raw audio into symbolic notations [13] .  ... 
doi:10.1145/2733373.2806383 dblp:conf/mm/LyuWZ15 fatcat:yop3t3tcw5apxbhk6gmn4puo5i

Pattern Discovery Techniques for Music Audio

Roger B. Dannenberg, Ning Hu
2003 Journal of New Music Research  
Several transcription methods are considered: monophonic pitch estimation, chroma (spectral) representation, and polyphonic transcription followed by harmonic analysis.  ...  These techniques can be used to perform an analysis of musical structure, as illustrated by examples.  ...  Matija Marolt offered the use of his SONIC transcription software, which enabled us to explore the use of polyphonic transcription for music analysis.  ... 
doi:10.1076/jnmr.32.2.153.16738 fatcat:zajlp6br4zakdf3askx32qmaiu

An End-to-End Neural Network for Polyphonic Piano Music Transcription

Siddharth Sigtia, Emmanouil Benetos, Simon Dixon
2016 IEEE/ACM Transactions on Audio Speech and Language Processing  
We present a supervised neural network model for polyphonic piano music transcription.  ...  We compare performance of the neural network based acoustic models with two popular unsupervised acoustic models.  ...  Abstract-We present a supervised neural network model for polyphonic piano music transcription.  ... 
doi:10.1109/taslp.2016.2533858 fatcat:gtea73lanbhdjpg6wbf3rocjwi

A holistic approach to polyphonic music transcription with neural networks [article]

Miguel A. Román, Antonio Pertusa, Jorge Calvo-Zaragoza
2019 arXiv   pre-print
Most previous Automatic Music Transcription (AMT) methods seek a piano-roll representation of the pitches, that can be further transformed into a score by incorporating tempo estimation, beat tracking,  ...  We present a framework based on neural networks to extract music scores directly from polyphonic audio in an end-to-end fashion.  ...  Note-level transcription goes a step further by estimating the notes characterized by their pitch and clock-time duration (onset and offset times), producing a piano-roll representation of the music.  ... 
arXiv:1910.12086v1 fatcat:utyjaa4zhzgprfefcnv77x6tae

Recurrent Neural Networks For Drum Transcription

Richard Vogl, Matthias Dorfer, Peter Knees
2016 Zenodo  
INTRODUCTION AND RELATED WORK Automatic music transcription (AMT) methods aim at extracting a symbolic, note-like representation from the audio signal of music tracks.  ...  While it is a first step towards drum transcription from polyphonic music, there also exist multiple applications for the transcription of solo drum tracks.  ... 
doi:10.5281/zenodo.1417612 fatcat:exfwx77uxfglrp6fhymduy3knm

Polyphonic Music Composition with LSTM Neural Networks and Reinforcement Learning [article]

Harish Kumar, Balaraman Ravindran
2019 arXiv   pre-print
We designed a representation that divides polyphonic music into a small number of monophonic streams.  ...  Promising results have been observed across a number of recent attempts at music composition using deep RNNs.  ...  This representation can embody polyphonic music of all forms and is limited in this process only by the number of streams n s and the set of permissible durations d. • During transcription, each incoming  ... 
arXiv:1902.01973v2 fatcat:aaobl2fzhjg67jtvnbcsap2zwa
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