Now the internet and machine translation are rendering them obsolete.

而现在，由于互联网和机器翻译的发展，它们开始逐渐过时。

Google Translate may be the best-known name in machine translation, but it often blunders.

谷歌翻译可能是机器翻译领域最广为人知的名字，但它经常出错。

Machine translation is not a new concept.

机器翻译并不是一个新概念。

Another method is statistical machine translation, which analyzes a database of books, articles, and documents that have already been translated by humans.

统计翻译法，这个方法是取分析那些已经被前人翻译过的书籍、文章和文件的数据库。

But we saw the potential to really change things like video indexing, machine translation, speech recognition.

但我们看到了真正改变视频索引、机器翻译、语音识别等事物的潜力。

However, traditional machine translation was limited as it largely relied on the manual input of vocabulary and terms.

然而，传统的机器翻译在很大程度上依赖于人工输入词汇和术语，具有一定的局限性。

Applying computers to language studies has resulted in machine translation systems and machines that recognize and produce speech and text.

将计算机应用于语言研究产生了机器翻译系统和机器，这些机器能够识别和产生语音和文本。

This makes it impossible to build machine translation tools using standard techniques, which require large amounts of written text in order to train an AI model.

这使得使用标准技术构建机器翻译工具成为不可能，而标准技术需要大量书面文本来训练 AI 模型。

Yet as Johnson's experiment shows, for most workaday purposes machine translation (MT) has got a lot better in the past five years or so.

然而，正如 Johnson 的实验所表明的那样，对于大多数日常用途而言，机器翻译 (MT) 在过去五年左右的时间里已经变得更好了。

Besides manual input of vocabulary list, the new machine translation software can learn through the comparison of parallel texts -two texts about the same topic but in two different languages.

除了人工输入词汇表，新的机器翻译软件还可以通过平行文本的比较学习，即两个关于相同主题，但两种不同语言的文本。

Not Limited to Language Education: While research in language education is a core component of applied linguistics, its scope extends beyond this. It covers areas such as language policy, translation, language pathology, machine translation, language planning, and more.

虽然语言教育研究是应用语言学的核心组成部分，但其范围超出了这一范围。它涵盖语言政策、翻译、语言病理学、机器翻译、语言规划等领域。