How Popular is Machine Translation Post-Editing?

机器翻译后期编辑有多受欢迎?

2024-08-05 09:20 slator

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On July 25, 2024, OpenAI announced the prototype version of SearchGPT, available only via waitlist. The move to asking an AI and getting an answer directly instead of a series of links to probe is very attractive. Whether the answer is correct or not is another matter. A lot of content showing up in search results is AI-made. OpenAI says SearchGPT’s answers will include sources, so will it be indirectly referencing itself? Odds are, yes, it will. Back in July 2024, we recounted the times we asked readers to tell us how their use of ChatGPT has evolved, and the latest question was how their use of that or other large language models (LLMs) had developed so far in 2024. In that poll, for a little over a third (33.3%) of readers the use had stayed the same. A bit later, when asked whether ChatGPT had affected their use of Google Search, most Slator readers chose the option consistent with that latest measure of general ChatGPT use: over two-thirds of respondents (65.7%) are still using mostly the search engine. Less than a quarter (22.9%) of readers reported using Google Search a bit, and ChatGPT more often. The rest (11.4%) said they mostly use ChatGPT for questions (but aren’t questions also searches?). When things are familiar to large sectors of the population, associating a graphic element with a concept is not difficult. For AI, it seems like the entire planet has agreed on the sparkle and the robot emojis to represent it. Explaining to your friends and relatives things like “prosody in cascade and direct speech-to-text translation” is… complicated. Even when you fully understand these concepts, the old diagram on a napkin might be far more eloquent than just your words. Language AI is in the hands and the hand-held devices of consumers. Naturally, as with other technologies, most can probably explain what the AI does, but not how it does it. The many comments on social media referring to AI features as being “like magic” are good indicators that the sparkle represents the concept for most quite well indeed. Those of us who have jobs in the language industry get the AI “how” questions. And most readers (51.1%) concur that explaining our jobs to family and friends still has the same level of difficulty, compared to three years ago. A little over a third (36.2%) of readers have found it harder to explain, and a small group (12.7%) thinks it is easier now. Machine translation post-editing (MTPE) has been around since, well, since machine translation (MT) has been around. All of this century so far and part of the last one. What is different as we enter the second half of 2024 is that MTPE surpasses editing of human translation. More domains once said to be impossible for AI to handle, such as literature and marketing copy, are also now being machine-translated and handed over to an expert-in-the-loop to polish up the result. The statement published by The Société française des traducteurs (SFT) in early July on AI, since removed from its website, was too little too late. The Society noted that 70% of its members consider post-editing a threat and that post-editing “ultimately creates mind-numbing fatigue,” is a “tedious task,” and is “very poorly remunerated.” We asked readers if they agreed that post-editing is tedious and mind-numbing, and most (61.2%) said yes. A little under a quarter of respondents (23.5%) said it is so sometimes, and a small group (10.2%) said it is if the wrong tools are used. A tiny group (5.1%) said they actually liked it. The weather is partly to blame when certain economic indicators fluctuate. In the language services industry, some indirect impact can be expected, for example, if the weather affects international supply chains. That has happened. A summer business slowdown, though, can impact any industry, weather and other major causes notwithstanding. What has not stopped is the influx of capital into parts of the industry, including AI dubbing and captioning, M&As, and the stream of announcements of new capabilities, LLM versions, or language additions by the usual players. We asked readers if they were seeing a summer slowdown in business, and while a quarter (25.8%) of respondents said they are busier than ever, the rest are split between a definite slowdown (40.3%) and business as usual (33.9%).
2024年7月25日,OpenAI宣布了SearchGPT的原型版本,仅通过waitlist提供。向人工智能提问并直接获得答案,而不是一系列链接进行探测的举动非常有吸引力。答案正确与否是另一回事。 搜索结果中显示的许多内容都是人工智能制造的。OpenAI表示SearchGPT的答案将包括来源,那么它会间接引用自己吗?很有可能,是的,会的。 早在2024年7月,我们就讲述了我们要求读者告诉我们他们对ChatGPT的使用是如何发展的,最新的问题是他们对该模型或其他大型语言模型(LLM)的使用在2024年迄今为止是如何发展的。在那次民意调查中,超过三分之一(33.3%)的读者使用保持不变。 过了一会儿,当被问及ChatGPT是否影响了他们对谷歌搜索的使用时,大多数Slator读者选择了与一般ChatGPT使用的最新衡量标准一致的选项:超过三分之二的受访者(65.7%)仍然主要使用搜索引擎。 不到四分之一(22.9%)的读者表示使用过谷歌搜索,更经常使用ChatGPT。其余的人(11.4%)说他们大多使用ChatGPT提问(但提问不也是搜索吗?). 当大部分人都熟悉事物时,将图形元素与概念联系起来并不困难。对于人工智能来说,似乎整个星球都同意用火花和机器人表情符号来代表它。 向你的朋友和亲戚解释像“级联中的韵律和直接语音到文本翻译”这样的事情是…复杂的。即使你完全理解了这些概念,餐巾上的旧图表可能比你的话更有说服力。 语言AI在消费者的手中和手持设备上。当然,与其他技术一样,大多数技术可能能够解释人工智能做什么,但无法解释它是如何做的。社交媒体上的许多评论将人工智能功能称为“像魔法一样”,这很好地表明sparkle确实很好地代表了大多数人的概念。 我们这些在语言行业工作的人会遇到人工智能“如何”的问题。大多数读者(51.1%)认为,与三年前相比,向家人和朋友解释我们的工作仍然有同样的难度。 略多于三分之一(36.2%)的读者发现解释起来更难了,一小部分人(12.7%)认为现在更容易了。 机器翻译后期编辑(MTPE)自从机器翻译(MT)出现以来就一直存在。本世纪到目前为止,也是上个世纪的一部分。进入2024年下半年,不同的是,MTPE超越了人工翻译的编辑。 更多曾经被认为人工智能不可能处理的领域,如文学和营销文案,现在也被机器翻译,并交给一位专家来完善结果。 法国翻译协会(SFT)7月初发表的关于人工智能的声明(自其网站上删除)太少也太晚了。该协会指出,70%的成员认为后期编辑是一种威胁,后期编辑“最终会造成令人麻木的疲劳”,是一项“乏味的任务”,而且“报酬非常低”。 我们询问读者是否同意后期编辑是乏味和麻木的,大多数人(61.2%)说是的。不到四分之一的受访者(23.5%)表示有时会如此,一小部分人(10.2%)表示,如果使用了错误的工具,就会如此。一小部分人(5.1%)说他们实际上喜欢它。 当某些经济指标波动时,天气是部分原因。在语言服务行业,一些间接影响是可以预期的,例如,如果天气影响国际供应链。这已经发生了。 然而,夏季商业放缓可能会影响任何行业、天气和其他主要原因。没有停止的是资本涌入该行业的部分领域,包括人工智能配音和字幕、并购,以及通常参与者宣布的新功能、LLM版本或语言添加。 我们询问读者是否看到夏季业务放缓,虽然四分之一(25.8%)的受访者表示他们比以往任何时候都更忙,但其余的人则分为明确放缓(40.3%)和一切如常(33.9%)。

以上中文文本为机器翻译,存在不同程度偏差和错误,请理解并参考英文原文阅读。

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