Semantic Scholar Open Access 2012 724 sitasi

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

Nicolas Boulanger-Lewandowski Yoshua Bengio Pascal Vincent

Abstrak

We investigate the problem of modeling symbolic sequences of polyphonic music in a completely general piano-roll representation. We introduce a probabilistic model based on distribution estimators conditioned on a recurrent neural network that is able to discover temporal dependencies in high-dimensional sequences. Our approach outperforms many traditional models of polyphonic music on a variety of realistic datasets. We show how our musical language model can serve as a symbolic prior to improve the accuracy of polyphonic transcription.

Penulis (3)

N

Nicolas Boulanger-Lewandowski

Y

Yoshua Bengio

P

Pascal Vincent

Format Sitasi

Boulanger-Lewandowski, N., Bengio, Y., Vincent, P. (2012). Modeling Temporal Dependencies in High-Dimensional Sequences: Application to Polyphonic Music Generation and Transcription. https://www.semanticscholar.org/paper/07c43a3ff15f2104022f2b1ca8ec4128a930b414

Akses Cepat

PDF tidak tersedia langsung

Cek di sumber asli →
Lihat di Sumber
Informasi Jurnal
Tahun Terbit
2012
Bahasa
en
Total Sitasi
724×
Sumber Database
Semantic Scholar
Akses
Open Access ✓