Samir Sadok

Distinct training objectives in self-supervised speech models create unique acoustic compression regimes that impact downstream task performance.

Encoding phonetic classes can dramatically improve the accuracy of 3D facial animation, unlocking new possibilities for realistic speech-driven avatars.

Decoupling shape and gain in neural audio codecs slashes bitrate and complexity, offering a more efficient way to encode audio.