好英语网今晚会和伴侣吵架吗？人工智能帮你预测
Let’s say your relationship is on the rocks. You’ve been trying to work things out together in couples’ counselling, but ultimately, you want to know if it is worth the effort. Will things get better, or are they doomed to fall apart?
假设你们的关系出现了问题，并且一直在进行婚姻咨询尝试解决，但你还是想知道这样做到底值不值得——你们能重归于好吗？还是说分手已成定局？
It might be worth just pausing for a second to listen to your partner. Really listen. When you speak to each other, your voices hold all sorts of information that could reveal the answer. Subtle inflections in tone, the pauses between phrases, the volume at which you speak – it all conveys hidden signals about how you really feel.
停下来聆听伴侣的声音也许值得一试，并且是真正的聆听。与伴侣交谈时，声音里包含的各种信息能解答你的疑惑。语调的微妙变化、语句之间的停顿以及说话的音量，这些都传达了你藏于内心的真实感受。
A lot of this we pick up on intuitively. We use it to fine-tune the meaning of our words. Think of the difference between these questions:
很多时候我们都是凭直觉来调整句子的意思。想想下面这几个问句之间的区别（粗体字表重音）：
“Why are you here?”
“你为什么在这里？”
“Why are you here?”
“你为什么在这里？”
“Why are you here?”
“你为什么在这里？”
That shift in emphasis is one of the more obvious ways we layer our speech with meaning. But there are many more layers that we add without realising it.
改变句子的重音是表达不同意思最明显的方式之一，但有时候我们会在意识不到的情况下增添更多内含。
But there is a way to extract this hidden information from our speech. Researchers have even developed artificial intelligence that can then use this information to predict the future of couples’ relationships. The AI is already more accurate at this than professionally trained therapists.
有种方法可以从对话中提取出隐藏的信息，研究人员甚至已经在利用人工智能分析这些信息来预测伴侣的关系。在这方面，人工智能的预测已经比训练有素的治疗师更准确。
In one study, researchers monitored 134 married couples who had been having difficulties in their relationships. Over two years, the couples each recorded two 10-minute problem-solving sessions. Each partner chose a topic about their relationship that was important to them and discussed them together. The researchers also had data on whether or not the couples’ relationships improved or deteriorated and if they were still together two years later.
在一项研究中，研究人员观察了134对婚姻出现问题的夫妻。在两年多的时间里，每对夫妻各录下两次解决问题的过程，选择一个关乎两人关系的重要话题一起讨论，每段视频十分钟。研究人员还知道这些夫妻的关系是有所改善还是更加恶化了，以及两年后他们是否还在一起。
Trained therapists watched videos of the recordings. By assessing the way the couples spoke to each other, what they said and how they looked while they were talking, the therapists made a psychological assessment about the likely outcome of their relationship.
训练有素的治疗师看了这些视频后，通过分析夫妻之间说话的方式、内容以及说话时的表情，对两人关系可能产生的结果进行了心理评估。
The researchers also trained an algorithm to analyse the couples’ speech. Previous research had given the team some clues that certain features were likely to be involved in human communication, such as intonation, speech duration and how the individuals took turns to speak. The algorithm’s job was to calculate exactly how these features were linked to relationship strength.
研究人员则编写了一套算法来分析夫妻之间的对话。之前的研究已经表明，人类的对话交流包含了若干特征，比如语调、说话时长以及两人交替说话的情况。该算法的任务是准确计算出这些特征与关系持久性之间的联系。
The algorithm was purely based on the sound recordings, without considering visual information from the videos. It also ignored the content of their conversations – the words themselves. Instead, the algorithm picked up on features like cadence, pitch and how long each participant talked for.
该算法完全基于录音，没有使用视频中的图像信息，也没有考虑谈话内容即话语本身。它提取的特征包括抑扬顿挫、音调以及每个人说话的时长。
Amazingly, the algorithm also picked up on features of speech beyond human perception. These features are almost impossible to describe because we’re not typically aware of them – such as spectral tilt, a complex mathematical function of speech.
令人惊讶的是，该算法还提取出了一些人类感知不到的语音特征。这些特征几乎无法用语言描述，因为我们并意识不到它们的存在。比如谱斜率，一个复杂精准的语言功能。
“Using lots of data, we can find patterns that may be elusive to human eyes and ears,” says Shri Narayanan, an engineer at the University of Southern California, who led the study.
领导这项研究的南加州大学工程师纳拉亚南（Shri Narayanan）说：“通过分析大量的数据，我们可以发现人类眼睛和耳朵所难以摸透的模式。”
After being trained on the couples’ recordings, the algorithm became marginally better than the therapists at predicting whether or not couples would stay together. The algorithm was 79.3% accurate.
算法经过这些夫妻录音的训练后，预测伴侣是否会继续在一起的准确率为79.3%，略高于治疗师。
The therapists – who had the advantage of also being able to understand the content of the couples’ speech and watching their body language – came in at 75.6% accurate.
治疗师的准确率为75.6%，他们的优势在于能够理解夫妻间谈话的内容，并观察他们的肢体语言。
“Humans are good at decoding many pieces of information,” says Narayanan. “But we can’t process all aspects of information available.”
“人类善于解码许多信息片段，”纳拉亚南说：“但无法处理信息包含的全部内容。”
The idea is that we are ‘leaking’ more information about our thoughts and emotions than we, as humans, can pick up on. But algorithms are not just restricted to decoding the voice features that people tend to use to convey information. In other words, there are other ‘hidden’ dimensions to our speech that can be accessed by AI.
这表示人类所“泄露”的思想和情感信息比能察觉到的要多。算法不仅仅局限于解码人们用来传达信息的声音特征，换句话说，人工智能可以获取人类语言中其他“隐藏”维度上的内容。
“One the advantages of computers is their ability to find patterns and trends in large amounts of data,” says Fjola Helgadottir, a clinical psychologist at the University of Oxford. “Human behaviour can give insight into underlying mental processes,” she says.
牛津大学的临床心理学家海尔达多提尔（Fjola Helgadottir）说：“计算机的优势之一是能够在海量数据中发现模式和趋势，分析人类行为可以使我们洞悉潜在的心理过程。”
“However, machine learning algorithms can do the hard work of sorting through, finding pertinent information, and making a prediction about the future.”
“机器学习算法可以完成一些艰苦工作，比如整理、查找相关信息和预测未来。”
An algorithm that predicts whether or not your relationship is doomed may not be the most appealing idea. Especially as it is only three-quarters accurate, at present. Such a prediction could conceivably change the course of your relationship and how you feel about your partner.
用算法预测伴侣关系的走向可能听上去并不非常吸引人，特别是目前它的准确率只有四分之三。这种预测很可能会改变你们关系的进程，以及你对伴侣的感觉。
But cracking the information hidden in the way we talk – and in how our bodies function – could be used to make our relationships better.
但是，破解隐藏在我们说话方式和身体机能中的信息，也可以改善伴侣关系。
Theodora Chaspari, a computer engineer at Texas A&M University, has been developing an AI program that can predict when conflict is likely to flare up in a relationship. Chaspari and her colleagues used data from unobtrusive sensors – like a wrist-worn fitness tracker – that 34 couples wore for a day.
德州农工大学的计算机工程师查斯帕里（Theodora Chaspari）一直在从事人工智能的开发，来预测一段关系中什么时候会爆发冲突。她和同事们用一种不显眼的传感器收集数据，有点像是个健康手环，有34对伴侣会将这种传感器佩戴一天。
The sensors measure sweat, heartrate and voice data including tone of voice, but also analysed the content of what the couples said – whether they used positive or negative words. A total of 19 of the couples experienced some level of conflict during the day that they wore the sensors.
传感器会测量汗液、心率和声音数据，譬如语调，还会分析伴侣们说的话，用词是积极的还是消极的。共有19对伴侣在佩戴传感器的当天发生了不同程度的冲突。
Chaspari and her colleagues used machine learning to train an algorithm to learn the patterns associated with arguments that the couples reported having. After being trained on this data, the algorithm was able to detect conflict in other couples using just the data from the sensors, with an accuracy of 79.3%.
查斯帕里和同事们利用机器学习编写出了一套算法来分析这些伴侣间的争吵。经过训练，算法仅利用传感器的数据就能检测出其他伴侣是否会发生冲突，准确率为79.3%。
Now the team is developing predictive algorithms that they hope to use to give couples a heads-up before an argument is likely to take place by detecting the warning signs that lead up to one.
目前，研究小组正在开发一种预测型算法，希望通过检测导致争吵的因素，在争吵发生之前发出预警信号。
The way the authors foresee it working is like this: you’ve had a busy day at work, perhaps had a stressful meeting, and you’re on your way home. Your partner has also had a tough day. By monitoring both of your perspiration levels, heart rates and the way you’ve been speaking in the past hours, the algorithm would make a calculation of how likely it is that you’ll face friction with an equally exasperated partner when you get home.
这种算法未来可能是这样工作的：你正在回家的路上，忙了一整天可能还开了个糟心的会，你的另一半这天也不好过。通过监测你的出汗量、心率和过去几个小时的说话方式，该算法可以计算出，你回家后与心情同样不好的伴侣发生摩擦的可能性有多大。
“At this point, we can intervene in order to resolve the conflict in a more positive way,” says Chaspari.
查斯帕里说：“这个时候，我们就可以介入，用更加积极的方式解决冲突。”
This could be done by simply sending a message to couples before the moment heats up, says Adela Timmons, a psychologist on the project based at the Clinical and Quantitative Psychology Center for Children and Families at Florida International University.
心理学家蒂蒙斯（Adela Timmons）目前在佛罗里达国际大学的儿童与家庭临床及定量心理学中心参与研究项目，她表示，只要在冲突升级之前给伴侣们发条信息就行了，就这么简单。
“We think that we can be more effective in our treatments if we’re able to administer them in people’s real lives at the points that they need them most,” she says.
她说：“如果能在现实生活中人们最需要的时候给予帮助，我们的工作就会更有效。”
The traditional model of therapy isn’t capable of fulfilling that goal. Typically, a session might take place for an hour a week, when the patients recall what happened since the last session, and talk through problems that arose.
传统的治疗方法做不到。咨询通常是每周一小时，咨询者回忆上一次咨询后发生的事情，并讨论出现的问题。
“The therapist isn’t able to be there in the moment when someone actually needs the support,” says Timmons. “There are a lot of steps in the traditional process where the intervention can break down and be less effective.”
蒂蒙斯说：“在人们最需要帮助的时候，治疗师无法在场。在传统干预中很多步骤会失效，效果也就不如预期。”
But an automated prompt based on consistently monitoring people’s physiology and speech could fulfil the real-time dream of therapy intervention. It could also allow for a more standardised form of treatment, says Helgadottir.
但海尔达多提尔表示，持续监测人们的生理状况和语言并自动发出提示可以实现实时干预，也能让治疗更加标准化。
“Nobody really knows what goes on in a closed therapy room,” says Helgadottir, who has developed an evidence-based platform using AI to treat social anxiety. “Sometimes the most effective techniques aren’t being used since they require more effort on the part of the therapist. On the other hand, the clinical components of AI therapy systems can be completely open and transparent.
“没人知道封闭的治疗室里是什么情况， 有时治疗师并没有使用最有效的方法，因为会比较麻烦。但人工智能治疗系统的临床步骤可以做到完全公开透明。”海尔达多提尔说。她开发了一个以实证为基础的平台，利用人工智能治疗社交焦虑。
“They can be designed and reviewed by the leading researchers and practitioners in the field. Furthermore, computers don’t have off days, and there is no difference if 1, 100 or 1,000 users are benefitting at the same time.”
“该领域优秀的研究人员和从业者都可以设计并审查治疗系统。而且电脑不用休息，处理1100和1000名咨询者在工作量上并没有什么区别。”
There are potential pitfalls though. There’s no guarantee that a ping from your phone warning of an impending argument won’t backfire and wind you up even more. The timing of the intervention is crucial.
不过也存在隐患。并不能保证在手机上收到“争吵即将爆发”的提示不会适得其反，信息可能会让你更加紧张，所以干预的时机至关重要。
“We probably don’t want to actually intervene during a conflict, says Timmons. “If people are already upset, they aren’t going to be terribly receptive to prompts on their phone that they should calm down. But if we can catch people in the period where it’s starting to escalate but they haven’t lost their capacity to regulate their behaviour – that’s the sweet spot of intervention.”
蒂蒙斯说：“我们不想在冲突进行时进行实际干预。如果人们已经心情很差，手机上收到让他们冷静的提示也没那么容易接受。在冲突升级前，在他们还没有失去控制力时进行干预，这才是最佳时机。”
There are plenty of technological hurdles left to overcome before an app like this can be rolled out. The team needs to refine its algorithms and test their efficacy on a wider range of people. There are also big questions around privacy.
在推出这样的应用程序之前，还需要克服很多技术障碍。开发团队需要不断改进算法，并在更广泛的人群中测试其有效性。此外还有一些关于隐私的重要问题。
具有预测能力的人工智能可以帮助想要改善关系的夫妻。
A data breach of a device storing data on your relationship with your partner would put a lot of sensitive information at risk. One could also question what would happen to the data if there was an alleged crime, such as domestic violence.
存储伴侣关系的数据一旦泄露，许多敏感信息都有被曝光的风险。人们还质疑，如果发生了犯罪，比如家庭暴力，这些数据该如何处理。
“We have to think about how we would handle those situations and ways to keep people safe while protecting their privacy,” says Timmons. “Those are wider social issues that we will continue to discuss.”
蒂蒙斯说：“我们必须思考如何应对这些情况，保护人们的隐私和安全。我们会继续讨论这些更加广泛的社会问题。”
If this model of therapy is indeed successful, it could also open doors to similar ways to improve other kinds of relationships – such as within the family, at work, or the doctor-patient dynamic. The more that our different bodily systems are monitored – from our eye movements to our muscle tension – the more could be revealed about what is in store for our relationships. There may prove to be many more layers of meaning, beyond our speech and basic physiological reactions, that can best be decoded by machines.
这种治疗模式如果真的成功了，也会为改善其他关系打开一扇大门，比如家庭、工作或医患关系。我们身体的不同情况（从眼球运动到肌肉紧张）受到的监控越多，就越能揭示出关系中隐藏的信息。除了语言和基本的生理反应之外，机器可以解码对话中更丰富的含义。
