7 citations · 21 across the 9 of their papers we have counts for
9 papers
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…
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…
Voice-preserving Zero-shot Multiple Accent Conversion
Mumin Jin, Prashant Serai, Jilong Wu +3
Most people who have tried to learn a foreign language would have experienced difficulties understanding or speaking with a native speaker's accent. For native speakers, understand…
Towards zero-shot Text-based voice editing using acoustic context conditioning, utterance embeddings, and reference encoders
Jason Fong, Yun Wang, Prabhav Agrawal +4
Text-based voice editing (TBVE) uses synthetic output from text-to-speech (TTS) systems to replace words in an original recording. Recent work has used neural models to produce edi…
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…
Direct speech-to-speech translation with discrete units
Ann Lee, Peng-Jen Chen, Changhan Wang +9
We present a direct speech-to-speech translation (S2ST) model that translates speech from one language to speech in another language without relying on intermediate text generation…