Most interviewees rated machine translation quality as relatively poor and used it only for gist

Description #

When interviewees' knowledge, attitudes, and beliefs toward machine translation were gauged, more than half reported having used online MT software (e.g., Google Translate or Bing Translator) in the past, but most had used it only a handful of times and about half of those users did so for personal purposes, mostly to get the "gist" of translated information. Regardless of their extent of use, the majority described the quality of MT output as relatively poor, and this negative impression of quality was prevalent across both health departments.

"Most had used MT software only a handful of times. About half of those who had used MT had done so for personal use, mostly to get the "gist" of translated information." (Turner, 2015, p. 142)

"Regardless of use, the majority of interviewees described the quality of MT translations as relatively poor." (Turner, 2015, p. 142)

Methods Context #

What? #ⓘ

The observable: interviewees' knowledge, attitudes, and beliefs toward machine translation, including their appraisal of MT output quality.

"We gauged interviewees' knowledge, attitudes, and beliefs toward MT." (Turner, 2015, p. 142)

How? #ⓘ

Attitudes toward automation were elicited within the semi-structured interviews (which explicitly asked about attitudes toward using MT) and coded as an "attitudes towards automation" theme.

"the interviewees were asked questions regarding the social, physical, and political contexts of translation work; information processes, tasks, resources, and key decisions involved in the translation of health promotion materials; barriers and facilitators to translation activities; and attitudes towards using MT to produce multilingual materials [37]." (Turner, 2015, p. 138)

Who? #ⓘ

The 34 interviewees at PHSKC and WA DOH, of whom more than half had prior hands-on experience with online MT software.

"More than half of the interviewees at PHSKC and WA DOH had used online MT software (such as Google Translate or Bing Translator) in the past." (Turner, 2015, p. 142)

Other Notes #

This is an attitudinal (perceived-quality) finding from public-health practitioners, not a blinded measurement of MT output accuracy; the authors' separate accuracy study [29] found generic MT semantic adequacy averaged 4.19/5, so practitioner skepticism partly exceeds measured quality.