3 citations · 3 across the 3 of their papers we have counts for
3 papers
eess.AS2023
Self-Supervised Representations for Singing Voice Conversion
Tejas Jayashankar, Jilong Wu, Leda Sari +3
A singing voice conversion model converts a song in the voice of an arbitrary source singer to the voice of a target singer. Recently, methods that leverage self-supervised audio r…
cs.CL2023★ 3 cited
Synthetic Cross-accent Data Augmentation for Automatic Speech Recognition
Philipp Klumpp, Pooja Chitkara, Leda Sarı +5
The awareness for biased ASR datasets or models has increased notably in recent years. Even for English, despite a vast amount of available training data, systems perform worse for…
cs.SD2021
VocBench: A Neural Vocoder Benchmark for Speech Synthesis
Ehab A. AlBadawy, Andrew Gibiansky, Qing He +3
Neural vocoders, used for converting the spectral representations of an audio signal to the waveforms, are a commonly used component in speech synthesis pipelines. It focuses on sy…