Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
6960516 | Speech Communication | 2018 | 29 Pages |
Abstract
The paper presents two generally applicable conclusions: i) systems that are designed to operate in noise will benefit from being trained on well-matched Lombard speech data, ii) the results of speech recognition evaluations that employ artificial speech and noise mixing need to be treated with caution: they are overly-optimistic to the extent that they ignore a significant source of mismatch but at the same time overly-pessimistic in that they do not anticipate the potential increased intelligibility of the Lombard speaking style.
Related Topics
Physical Sciences and Engineering
Computer Science
Signal Processing
Authors
Ricard Marxer, Jon Barker, Najwa Alghamdi, Steve Maddock,