Sometimes, Siri can’t even…

有时候，Siri甚至无法……

What formal semantics tells us

形式语义告诉我们什么

There’s an unwavering discourse phenomenon in applied linguistics that always zips right over my head: “donkey sentences.” Essentially, these are expressions containing pronouns that exist outside the antecedent of a conditional statement, despite the fact that they covary with other quantifying constituents inside.

应用语言学中有一种坚定不移的话语现象，总是在我脑海中浮现：“驴子句子”。 从本质上讲，这些是包含代词的表达式，尽管它们与内部的其他量化成分相互依存，但它们存在于条件语句的先行条件之外。

Doesn’t ring a bell? Here’s a basic example:

不敲钟吗？ 这是一个基本示例：

(1) Every artist who paints a picture frames it.

(1)每位画画的画家都将其画框。

The statement above features the personal pronoun “it” whose meaning and antecedent (“paints a picture”) are evident to you and me, but to those who study sentence structure…not so much, as visualized (incorrectly) below using first-order logic and free-variables:

上面的陈述以人称代词“ it”为特征，它对您和我很明显，但对那些研究句子结构的人却不那么明显，如下面使用一阶(不正确地)看到的那样逻辑和自由变量：

(2) ∀x(ARTIST(x) ∧ ∃y(PICTURE(y) ∧ PAINT(x,y)) → FRAME(x,y))

(2)∀X(ARTIST(x)的 ∧∃Y(PICTURE(Y)∧涂料(X，Y))→FRAME(X，Y))

Although this case of anaphoric reference may be somewhat convoluted, the preceding example has me pondering the related notion of deixis and its (future) role in interaction design.

尽管这种回指的情况可能有些复杂，但是前面的示例让我思考了相关的概念ixix及其在交互设计中的(未来)作用。

Deitic expressions tell us everything about context in relation to the speaker, including tidbits about location, people, and time. When we talk about position, what words do we use? “Here” and “there” convey place. Perhaps “this street” or “that city” — more precise noun phrases that, regardless of their idiosyncrasy, provide us with spatial insight through and through. However, these points of locality are dependent on the active party, not the passive listener or reader.

言语表达可以告诉我们有关说话者背景的所有信息，包括有关地点，人员和时间的花絮。 当我们谈论职位时，我们使用什么词？ “这里”和“那里”传达的地方。 也许是“这条街”或“那个城市”-更精确的名词短语，无论它们的特质如何，始终为我们提供空间洞察力。 但是，这些本地性点取决于主动方，而不是被动的侦听器或阅读器。

Key point: “Here” is to you in Los Angeles, but “there” is to your friend in Oslo. To me, I am “I,” but to you, I am “you.” January 7, 2019, is “today” today, but on January 8, 2019, it’s “yesterday” today.

重点：“在这里”是给你在洛杉矶，但是“那里”是给你在奥斯陆的朋友。 对我来说，我是“我”，但对你来说，我是“你”。 2019年1月7日是今天的“今天”，但是在2019年1月8日是今天的“昨天”。

Applying deixis to voice assistants

将Deixis应用于语音助手

We ask Siri to call our moms, play the new Ariana song, tell us a joke. Alexa can switch on your foyer lights with ease, ignite the fireplace on a bone-chilling night, and power up the vacuum cleaner. Okay, great. But what if I point? Snap? Whistle? Dart my eyes at my TV? Nothing but automated apologies.

我们要求Siri打电话给我们的妈妈，播放Ariana的新歌，给我们讲个笑话。 Alexa可以轻松打开门厅灯，在令人毛骨悚然的夜晚点燃壁炉，并打开真空吸尘器的电源。 好，太棒了。 但是，如果我指出呢？ Snap？ 哨？ 用我的眼睛看电视吗？ 除了自动道歉。

Why is that? The former are voice-activated requests. This is what Siri and Alexa do for a living: react and respond to your coherent, logical, syntactically accurate commands, questions, and statements. By gesticulating at the television, you’re adding an additional element while erasing vital linguistic context clues and replacing definite nouns with pronouns. This is why deixis matters.

这是为什么？ 前者是语音激活的请求。 这就是Siri和Alexa谋生的方式：对您连贯，逻辑，句法准确的命令，问题和陈述做出React并做出回应。 通过在电视上打手势，您将添加一个附加元素，同时消除了重要的语言上下文线索，并用代词代替了定名词。 这就是为什么Deixis很重要。

Here’s a real-life scenario involving motion. You’re walking past 7-Eleven and ask your device, “How much does a 12-ounce Slurpee® cost there?” Upon posing the question, you simultaneously glance over at 7-Eleven a mere 10 feet from you. In this instance, 7-Eleven has been reduced to the determiner “there” and assigned an eye movement by the user. Fast-forward years from now and your gizmo might catch that brief instance of eye contact with 7-Eleven, spitting out “$0.80” on the cent. Unspooling it today, however, the deitic expression “there” among others are beyond cryptic to your voice assistant. Instead, your device will likely accommodate your inquiry by pulling up thousands of web results — its workaround, what it was programmed to do when interpreting muddled directives.

这是一个涉及运动的真实场景。 你走过去的7-Eleven和问问你的设备，“多少钱一个12盎司Slurpee®成本呢 ？” 提出问题后，您便同时瞥了一眼距离您仅10英尺的7-11。 在这种情况下，7-11已简化为确定器“那里”，并由用户分配了眼睛运动。 从现在算起快进几年了，您的小发明可能会与7-11眼神接触，从而花掉“ 0.80美元”。 但是，今天要进行后台处理时，您的语音助手所用的修饰语“那里”绝非易事。 取而代之的是，您的设备可能会通过提取成千上万的Web结果来满足您的查询要求-它的变通方法是它在解释混乱的指令时所进行的编程。

Understandably, gesture is tough due to the utter complexity of kinetics and motion detection. There are certainly aspects of deixis that voice recognition software can parse here and now, though principally in a unilateral fashion and with little intricacy. Try asking Siri where Portland is located. It will map Portland for you. Easy! Follow up with a question about the weather: “What’s the weather there this week?” You’re presented with the weekly forecast. Good! Now, revert to your first question using only a pronoun: “Where is it?” Here, “it” refers to the city of Portland, yet “it” escapes Siri: “I don’t have any places to show.” Siri cannot alter course and discern that “it” is Portland, even though Portland acted as the antecedent in round two.

可以理解，由于动力学和运动检测的完全复杂性，手势很难。 语音识别软件当然可以在现在和现在解析的Deixis的某些方面，尽管主要以单方面的方式并且几乎没有复杂性。 尝试问Siri波特兰在哪里。 它将为您映射波特兰。 简单！ 跟进有关天气的问题：“本周那里的天气如何？” 系统会为您提供每周预测。 好！ 现在，仅使用代词回到您的第一个问题：“它在哪里？” 在这里，“它”指的是波特兰市，但“它”却避开了Siri：“我没有可展示的地方。” 即使在第二轮中波特兰担任先例，Siri也无法改变路线并辨别“它”是波特兰。

Proximity, distality, and spaces far more confusing

邻近，远端和空间更加令人困惑

Determiners can be incredibly bewildering, too, even outside the field of voice recognition. Whilst intended to modify a noun, the English determiners “this” and “that” are often used interchangeably by native speakers…and not always accurately. Remember that prescriptivists assert “this” should be used to indicate proximity, whereas “that” ought to signify distance. Semantics complicates this quandary even further in English, where determiners may represent concrete nouns (“that turnip”) or abstract nouns (“those nightmares”).

即使在语音识别领域之外，确定者也可能会令人困惑。 意图修饰名词时，英语谓词“ this”和“ that”通常由母语人士互换使用，但并不总是准确。 请记住，规定主义者断言“这个”应该用来表示接近，而“那个”应该表示距离。 语义学使英语中的这个难题更加复杂，确定者可能代表具体名词(“那个萝卜”)或抽象名词(“那些噩梦”)。

And then we throw bilingualism into the mix. Although English uses a two-way referential distinction (“proximal” and “distal”), numerous languages encompass three or more layers for spatial deixis. Korean, for example, has a locution for an object near the speaker, a term for that near the listener, and yet another to denote something distant from both the speaker and the listener. (Fun fact: West Greenlandic has a whopping 12 layers, even a mode for objects that are invisible to the eye!) Ultimately, how L2 speakers relay these expressions into their non-native English dialects will vary from language to language and person to person — a tumultuous reality for UXers and designers alike.

然后，我们将双语制度加入其中。 尽管英语使用双向引用区别(“近端”和“远端”)，但许多语言都包含三层或更多层的空间指示。 例如，朝鲜语在说话者附近有一个对象的名词，在听者附近有一个名词，又一个词表示远离说话者和听者的事物。 (有趣的事实：西格陵兰岛有多达12层，甚至是肉眼看不见的物体的模式！)最终，第二语言的讲者如何将这些表达传达到他们的非母语英语方言中，将因语言而异，因人而异。 -对于UX用户和设计师来说都是一个动荡的现实。

These shortcomings — pertaining to gesture, ambiguity, or the many other factors that I failed to mention above — demonstrate how far we are from the pinnacle of voice interaction when it comes to deitic expressions and spatial orientation. Computational linguists and NLP professionals are essential in streamlining the interface for speech recognition software, such as by defining referents, as are designers by means of user research, complex usability testing, and GIS application development. Whether we examine this stumbling block from a linguistic standpoint or from that of design, ensuring deixis is wholly addressed for technology will remain a knotty endeavor no doubt.

这些缺点(与手势，歧义或我上面未提及的许多其他因素有关)表明，在语音表达和空间取向方面，我们离语音交互的顶峰有多远。 计算语言学家和NLP专业人员对于简化语音识别软件的界面至关重要，例如通过定义参考对象，设计师也需要通过用户研究，复杂的可用性测试和GIS应用程序开发。 无论是从语言学的角度还是从设计的角度来看待这个绊脚石，确保对技术完全解决Deixis仍然是一项艰巨的努力。

For those who work in HCI or UX, where do you believe studies will take us in 2020?

对于那些从事HCI或UX工作的人，您认为研究将在2020年将我们带到何处？

Zac Gipson is a senior management consulting analyst at Accenture Federal Services in Washington, D.C. His primary research interests center on machine translation, natural language processing, and voice user interface. He is also an OCB natural bodybuilder who is teaching others how to build lean muscle on a plant-based diet.

Zac Gipson是位于华盛顿特区的埃森哲联邦服务公司(Accenture Federal Services)的高级管理咨询分析师。他的主要研究兴趣集中在机器翻译，自然语言处理和语音用户界面上。 他还是OCB的自然健美运动员，他正在教别人如何以植物性饮食为基础锻炼肌肉。