Frank Cwitkowitz
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View article: Investigating an Overfitting and Degeneration Phenomenon in Self-Supervised Multi-Pitch Estimation
Investigating an Overfitting and Degeneration Phenomenon in Self-Supervised Multi-Pitch Estimation Open
Multi-Pitch Estimation (MPE) continues to be a sought after capability of Music Information Retrieval (MIR) systems, and is critical for many applications and downstream tasks involving pitch, including music transcription. However, existi…
View article: Toward Fully Self-Supervised Multi-Pitch Estimation
Toward Fully Self-Supervised Multi-Pitch Estimation Open
Multi-pitch estimation is a decades-long research problem involving the detection of pitch activity associated with concurrent musical events within multi-instrument mixtures. Supervised learning techniques have demonstrated solid performa…
Timbre-Trap: A Low-Resource Framework for Instrument-Agnostic Music Transcription Open
In recent years, research on music transcription has focused mainly on architecture design and instrument-specific data acquisition. With the lack of availability of diverse datasets, progress is often limited to solo-instrument tasks such…
View article: SynthTab: Leveraging Synthesized Data for Guitar Tablature Transcription
SynthTab: Leveraging Synthesized Data for Guitar Tablature Transcription Open
Guitar tablature is a form of music notation widely used among guitarists. It captures not only the musical content of a piece, but also its implementation and ornamentation on the instrument. Guitar Tablature Transcription (GTT) is an imp…
FretNet: Continuous-Valued Pitch Contour Streaming for Polyphonic Guitar Tablature Transcription Open
In recent years, the task of Automatic Music Transcription (AMT), whereby various attributes of music notes are estimated from audio, has received increasing attention. At the same time, the related task of Multi-Pitch Estimation (MPE) rem…
A Data-Driven Methodology for Considering Feasibility And Pairwise Likelihood in Deep Learning Based Guitar Tablature Transcription Systems Open
Guitar tablature transcription is an important but understudied problem within the field of music information retrieval. Traditional signal processing approaches offer only limited performance on the task, and there is little acoustic data…
Learning Sparse Analytic Filters for Piano Transcription Open
In recent years, filterbank learning has become an increasingly popular strategy for various audio-related machine learning tasks. This is partly due to its ability to discover task-specific audio characteristics which can be leveraged in …
Learning Sparse Analytic Filters for Piano Transcription Open
In recent years, filterbank learning has become an increasingly popular strategy for various audio-related machine learning tasks. This is partly due to its ability to discover task-specific audio characteristics which can be leveraged in …
A Data-Driven Methodology for Considering Feasibility and Pairwise Likelihood in Deep Learning Based Guitar Tablature Transcription Systems Open
Guitar tablature transcription is an important but understudied problem within the field of music information retrieval. Traditional signal processing approaches offer only limited performance on the task, and there is little acoustic data…
BeatNet: CRNN and Particle Filtering for Online Joint Beat Downbeat and Meter Tracking Open
The online estimation of rhythmic information, such as beat positions, downbeat positions, and meter, is critical for many real-time music applications. Musical rhythm comprises complex hierarchical relationships across time, rendering its…
BeatNet: CRNN and Particle Filtering for Online Joint Beat, Downbeat and Meter Tracking Open
The online estimation of rhythmic information, such as beat positions, downbeat positions, and meter, is critical for many real-time music applications. Musical rhythm comprises complex hierarchical relationships across time, rendering its…
A study of the robustness of raw waveform based speaker embeddings under mismatched conditions Open
In this paper, we conduct a cross-dataset study on parametric and non-parametric raw-waveform based speaker embeddings through speaker verification experiments. In general, we observe a more significant performance degradation of these raw…
Learning Sparse Analytic Filters for Piano Transcription Open
In recent years, filterbank learning has become an increasingly popular strategy for various audio-related machine learning tasks. This is partly due to its ability to discover task-specific audio characteristics which can be leveraged in …
BeatNet: CRNN and Particle Filtering for Online Joint Beat Downbeat and Meter Tracking Open
The online estimation of rhythmic information, such as beat positions, downbeat positions, and meter, is critical for many real-time music applications. Musical rhythm comprises complex hierarchical relationships across time, rendering its…