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Software Sniffs¹ Out Rat Squeaks²

Mice and rats vocalize. To us, many of the sounds they make are ultrasonic³—at too high a frequency to hear. But if we slow the calls down, they sound like squeaks. And not all squeaks are the same. The sounds that rodents⁵ make when they are excited versus⁶ disappointed can be quite different.

家鼠和大鼠发声。对我们来说，它们发出的许多声音都是超声波——频率太高而听不见。但是如果我们把声音放慢，它们听起来就像吱吱声。并不是所有的吱吱都是一样的。啮齿类动物兴奋和失望时发出的声音可能是完全不同的。

For example, here’s slowed-down audio of a rat drinking sugar water.

例如，这是一只老鼠喝糖水的慢放音频。

But this rat [different squeak] got played—it got non-sweetened water after becoming accustomed to sugar water.

但是这只老鼠(不同的吱吱声)玩了起来——它在习惯了糖水之后喝了不加糖的水。

“Calls around 22 kilohertz are usually associated with unhappy affect and calls around 55 kilohertz are happy affect.”

“大约22000赫兹的呼叫通常与不快乐的情绪有关，而大约55000赫兹的呼叫则是快乐的情绪。”

John Neumaier, a professor of psychiatry⁷ and pharmacology at the University of Washington.

John Neumaier，是华盛顿大学精神病学和药理学教授。

“So if you tickle⁸ a rat, it puts out a lot of 55 calls. If we give them a sucrose solution, then they put out a lot of calls at 55 kilohertz.”

所以，如果你给老鼠挠痒痒，它会发出55个声音。如果我们给它们蔗糖溶液，它们就会以55000赫兹的频率发出大量的叫声。”

Being able to interpret these different calls can help researchers understand the rodent⁴’s emotional state—which could affect the results of experiments on the animals.

能够解释这些不同的叫声可以帮助研究人员了解啮齿类动物的情绪状态，这可能会影响动物实验的结果。

Of course, listening to rodents in real time eats up resources. To code one hour of a recording⁹, “It takes 10 hours, you know, because you have to slow these recordings¹⁰ down in order to be able to listen to them.”

当然，实时聆听啮齿类动物的声音会消耗资源。一个小时的录音编码“需要10个小时，你知道，因为你必须放慢这些录音的速度，才能听到它们。”

To automate¹¹ the process, Neumaier’s associates, Kevin Coffey and Russell Marx, used machine algorithms originally designed for self-driving cars to develop software that they call DeepSqueak. The program takes recordings of rodent squeaks and plots them by frequency and intensity¹². By transforming the audio to a visual representation,"They were able to train the computer network to recognize what ultrasonic vocalization looks like and then to easily tell them apart from other kinds of noise."

为了实现这一过程的自动化，纽梅尔的同事凯文·科菲和拉塞尔·马克思使用了最初为自动驾驶汽车设计的机器算法来开发他们称之为DeepSqueak的软件。该项目记录啮齿动物吱吱的声音，并根据频率和强度绘制它们的分布图。通过把声音转换成视觉表现，“他们能够训练计算机网络识别超声波发声的样子，然后很容易地把它们与其他种类的噪音区分开来。”

The description of DeepSqueak is in the journal Neuropsychopharmacology.

DeepSqueak的描述发表在《神经精神药理学》杂志上。

The researchers have made the software available to any other scientists working with rodents who could use this kind of analysis.

研究人员已经将该软件提供给任何其他研究啮齿类动物的科学家，他们可以使用这种分析方法。

"In my mind it will democratize this kind of research so that people can afford to do it, because it's been a huge barrier."

“在我看来，这将使这类研究民主化，让人们能够负担得起，因为这是一个巨大的障碍。”