3 citations · 5 across the 4 of their papers we have counts for
5 papers
Jam-ALT: A Formatting-Aware Lyrics Transcription Benchmark
Ondřej Cífka, Constantinos Dimitriou, Cheng-i Wang +3
Current automatic lyrics transcription (ALT) benchmarks focus exclusively on word content and ignore the finer nuances of written lyrics including formatting and punctuation, which…
TONet: Tone-Octave Network for Singing Melody Extraction from Polyphonic Music
Ke Chen, Shuai Yu, Cheng-i Wang +3
Singing melody extraction is an important problem in the field of music information retrieval. Existing methods typically rely on frequency-domain representations to estimate the s…
Music SketchNet: Controllable Music Generation via Factorized Representations of Pitch and Rhythm
Ke Chen, Cheng-i Wang, Taylor Berg-Kirkpatrick +1
Drawing an analogy with automatic image completion systems, we propose Music SketchNet, a neural network framework that allows users to specify partial musical ideas guiding automa…
Deep Autotuner: a Pitch Correcting Network for Singing Performances
Sanna Wager, George Tzanetakis, Cheng-i Wang +1
We introduce a data-driven approach to automatic pitch correction of solo singing performances. The proposed approach predicts note-wise pitch shifts from the relationship between…
Deep Autotuner: A Data-Driven Approach to Natural-Sounding Pitch Correction for Singing Voice in Karaoke Performances
Sanna Wager, George Tzanetakis, Cheng-i Wang +3
We describe a machine-learning approach to pitch correcting a solo singing performance in a karaoke setting, where the solo voice and accompaniment are on separate tracks. The prop…