ESSV Konferenz Elektronische Sprachsignalverarbeitung

Title: In Articulation for Diversity

Authors: Korin Richmond


Research comes thick and fast these days - flurries of papers and a deluge of results. Amongst the swathes of work we can frequently discern similar, repeating themes though. This is no surprise because researchers, like people more generally, have long tended to converge on common methods and flock to the hot-topics of the day. But this does seem particularly true of work in the most recent past, and especially so in areas related to machine learning such as speech technology. This can be both beneficial, but also problematic. In this talk, I will couch this (somewhat philosophical!) issue within a mix of concrete research examples that span from the use of articulatory data for speech technology to signal processing.

Year: 2019
In session: Hauptvortrag
Pages: 83 to 83