Isn't the English language marvellous?
英语是极好的(marvellous),不是吗?
Some wouldn't say so, but for 20 years traditional British words have slowly been replaced by Americanisms。
有些人大[微博]概不会用“marvellous”这个词。但近20年来,传统的英式词汇已经逐渐被美式词汇所取代。
And now, words like 'marvellous' have been usurped by the US cliché: 'awesome'。
如今,“marvellous”等英式词汇已经被“awesome”等美式口语所取代。
The gradual change, charted by researchers at Cambridge University and Lancaster University, has also seen the decline of 'cheerio', 'pussy cat', 'marmalade' and 'fortnight', which are now barely used by anglophones。
剑桥大学和兰卡斯特大学的研究人员通过图表反映了这种语言现象的演变。根据图表,“cheerio”(再见)、“pussy cat”(小猫咪)、“marmalade”(果酱)等英式英语词汇的使用呈现下降趋势,几乎已被英语母语人士所抛弃。
While in the 1990s we were captivated by 'Walkmans', today it has been replaced by the likes of 'online' and 'smartphone'。
20世纪90年代风靡一时的“Walkman”(随身听)如今也被“online”(网上)和“smartphone”(智能手机)等新词所代替。
Other words like 'catalogue' and 'drawers', which were also regulars of the 1990s, have had to make way for 21st century sayings like 'Facebook', 'internet', 'Google', 'essentially' and 'treadmill'。
其他一些20世纪90年代的常用词,例如“catalogue”(目录)和“drawers”(抽屉),也不得不为21世纪的词汇让道,比方说“Facebook”(脸书)、“internet”(网络)、“Google”(谷歌)、“essentially”(本质上)和“treadmill”(跑步机)。
Figures show that in 2014 the word 'awesome' appears 72 times per million words compared to 'marvellous', which has fallen in use from 155 times per million 20 years ago to only two times per million today。
数据显示“awesome”一词在2014年的出现频率为72次/百万词,与之相比,“marvelous”的使用频率则从20年前的155次/百万词滑落到2次/百万词。
Researchers believe the digital revolution and America's growing influence on our culture have dramatically changed the way British people speak。
研究者认为,信息革命及美国日渐强势的文化影响力使英国人的口语产生了极大的变化。
Language expert Professor Tony McEnery, from the ESRC Centre for Corpus Approaches to Social Science (CASS) at Lancaster University, said: 'These very early findings suggest the things that are most important to British society are indeed reflected in the amount we talk about them。
兰卡斯特大学社会科学语料库方法ESRC中心的语言专家托尼·麦克恩尼利表示:“这些前期发现表明,什么才是对英国社会最重要的东西确实能够通过人们经常谈论的话题得到反映。”
'New technologies like Facebook have really captured our attention, to the extent that, if we're not using it, we're probably talking about it。
“Facebook等新兴科技产物确确实实地吸引了我们的注意力,即使在我们不使用它们的时候,我们也在讨论它们。”
'The rise of 'awesome' seems to provide evidence of American English's influence on British speakers.'
“awesome一词的崛起似乎证明了美式英语对英国人的影响。”
These are only the initial findings from a small pilot of the project, named the 'Spoken British National Corpus 2014', which is now underway。
以上仅是“2014年英国国家口语语料库”项目的一个试点项目的初步发现,该项目还处于开展阶段。
Prof McEnery said: 'We need to gather hundreds, if not thousands, of conversations to create a spoken corpus so we can continue to analyse the way language has changed over the last 20 years。
麦克恩尼利教授说:“我们需要搜集成千上万段日常对话来建立口语语料库,这样我们才能继续分析语言在近20年中的演变。”
'We are calling for people to send us MP3 files of their everyday, informal conversations in exchange for a small payment to help me and my team to delve deeper into spoken language.'
“我们让人们录下他们每天的非正式对话并把MP3文件寄给我们,相应地我们也会向他们支付一些报酬。这些文件可以帮助我和我的团队更加深入地研究口语。”
It is an ambitious project. Prof McEnery said: 'It has not been completed to this scale in the UK since the early 1990s。
这是一个宏大的项目。麦克恩尼利教授表示:“这是英国自20世纪90年代早期以来进行的最大规模的口语调查项目。”
'That data, which is now out of date, is still used by researchers from around the world today, so we know there is a real appetite for research of this kind。
“世界各地的研究者目前还在使用那些过时的资料,所以我们知道这次的研究项目非常有必要。”
'It is of great importance to collect new recordings from the 2010s in order to understand the nature of British English speech as it is today and not how it was more than two decades ago.'
“我们需要了解的是当下英式口语的特质,而非20多年前的,所以收集2010年以来的新的口语语料十分重要。
Using the 'Spoken British National Corpus 2014', the team at Lancaster University and Cambridge University Press will be able to shed light on the way our spoken language changes over time。
利用“2014年英国国家口语语料库”,兰卡斯特大学和剑桥大学出版社的研究团队最终将能向我们揭示英式口语的发展演变。
The research also allows analysis into language used in different regions, between genders and across different age groups。
该研究还对不同地区、不同性别和不同年龄层人群的语言进行了分析。