Name
Abstract | ||
|---|---|---|
In this paper, an automatic music transcription (AMT) algorithm based on a supervised non-negative matrix decomposition (NMD) is discussed. In particular, a novel approach for enhancing the sparsity of the solution is proposed. It consists of a two-step processing in which the NMD is solved joining a ℓ2 regularization and a threshold filtering. In the first step, the NMD is performed with the ℓ2 r... |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1109/TMM.2017.2674603 | IEEE Transactions on Multimedia |
Keywords | Field | DocType |
Music,Dictionaries,Matrix decomposition,Optimization,Instruments,Hidden Markov models,Software | Pattern recognition,Matrix (mathematics),Computer science,Matrix decomposition,Filter (signal processing),Speech recognition,Regularization (mathematics),Software,Artificial intelligence,Polyphony,Hidden Markov model | Journal |
Volume | Issue | ISSN |
19 | 7 | 1520-9210 |
Citations | PageRank | References |
1 | 0.40 | 21 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Antonello Rizzi | 1 | 363 | 41.68 |
| Mario Antonelli | 2 | 5 | 1.15 |
| Massimiliano Luzi | 3 | 3 | 1.49 |