A real-time music-scene-description system: predominant-F0 estimation for detecting melody and bass lines in real-world audio signals
By Masataka Goto. Speech Communication, 2004
385 citations recorded by the source corpus.
Subfields: Computer Vision and Pattern Recognition, Signal Processing
View Paper: https://www.semanticscholar.org/paper/ae82a8d8f7a2dbb8e063be02336587ce57ec6937
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Computer Vision and Pattern Recognition
- Emmanouil Benetos
- Justin Salamon
- Anssi Klapuri
- Emilia G'omez
- Dimitrios Giannoulis
- Holger Kirchhoff
- Remco C. Veltkamp
- Malcolm Slaney
In Signal Processing
- Emmanouil Benetos
- Justin Salamon
- Emilia G'omez
- Dimitrios Giannoulis
- Holger Kirchhoff
- Anssi Klapuri
- Simon E. Dixon
- Malcolm Slaney
Citations in the corpus
- Melody Extraction From Polyphonic Music Signals Using Pitch Contour Characteristics (2012, methodology): “STFT which has a fixed time–frequency resolution [4], [10], [20].”
- Content-Based Music Information Retrieval: Current Directions and Future Challenges (2008, methodology): “In 1999, Goto [43], [ 44 ] proposed a real-time method called PreFEst (Predominant-F0 Estimation method) which detects the melody and bass lines in monaural sound mixtures.”
- Automatic music transcription: challenges and future directions (2013, methodology): “An example of MAP estimation-based transcription is the PreFEst system (Goto 2004), where each harmonic is modelled by a Gaussian centered at its position on the log-frequency axis.”