3 citations · 4 across the 3 of their papers we have counts for
3 papers
eess.AS2023★ 1 cited
Towards Selection of Text-to-speech Data to Augment ASR Training
Shuo Liu, Leda Sarı, Chunyang Wu +4
This paper presents a method for selecting appropriate synthetic speech samples from a given large text-to-speech (TTS) dataset as supplementary training data for an automatic spee…
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…