How does end-to-end speech recognition training impact speech enhancement artifacts?

no code implementations • 20 Nov 2023 • Kazuma Iwamoto, Tsubasa Ochiai, Marc Delcroix, Rintaro Ikeshita, Hiroshi Sato, Shoko Araki, Shigeru Katagiri

Jointly training a speech enhancement (SE) front-end and an automatic speech recognition (ASR) back-end has been investigated as a way to mitigate the influence of \emph{processing distortion} generated by single-channel SE on ASR.

Automatic Speech Recognition Automatic Speech Recognition (ASR) +2

How Bad Are Artifacts?: Analyzing the Impact of Speech Enhancement Errors on ASR

no code implementations • 18 Jan 2022 • Kazuma Iwamoto, Tsubasa Ochiai, Marc Delcroix, Rintaro Ikeshita, Hiroshi Sato, Shoko Araki, Shigeru Katagiri

The artifact component is defined as the SE error signal that cannot be represented as a linear combination of speech and noise sources.

Automatic Speech Recognition Automatic Speech Recognition (ASR) +2