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清晰理解主语注意主语修饰语注意集合名词多做练习 主谓一致性是英语语法中的基础且核心规则之一，它要求主语和谓语在数（单数或复数）和人称（第一人称、第二人称、第三人称）上保持一致。然而，在实际应用中，由于各种原因，学生们常常在这一点上犯错。以下是几种避免主谓一致性错误的策略： 1. 清晰理解主语：首先，要清晰地识别出句子的主语。主语通常是句子开头的名词或名词短语，它执行了谓语的动作或表示了谓语的状态。例如，在“The cat sleeps on the mat”中，“The cat”就是主语。 2. 了解主语的数：主语可以是单数也可以是复数。主语的数决定了谓语的数。例如，“The cat sleeps”（猫睡觉）中的主语是单数，所以谓语也是单数。而“The cats sleep”（猫们睡觉）中的主语是复数，所以谓语也是复数。 3. 注意主语修饰语：有时候，主语后面会有一些修饰语，如“together with”，“along with”，“as well as”等，这些修饰语并不改变主语的数。例如，“The teacher, along with the students, is happy.”即使“the students”是复数，但主语“The teacher”是单数，所以谓语也是单数。
抗遗忘英语单词速记 5. 理解从句结构：在复杂的句子中，主语可能并不在句子的开头，而是在从句中。这时，我们需要找到真正的主语，并根据它的数和人称来确定谓语的形式。 6. 多做练习：最后，通过大量的阅读和写作练习来巩固主谓一致性的规则。只有通过实践，我们才能真正掌握这一规则，避免在实际应用中出现错误。 总的来说，避免主谓一致性错误的关键是清晰地理解句子的结构，准确地识别出主语，并根据主语的数和人称来正确地选择谓语的形式。通过不断的练习和实践，我们可以逐渐提高我们的英语水平，减少这类错误的发生。 For people who are unable to speak, signals of what they’d like to say hide in their brains. No one has been able to understand those signals directly. But researchers recently made progress in turning data from electrodes (电极) surgically placed on the brain into computer-made speech. Using computer models known as neural (神经) networks (NN), they reconstructed words and sentences that were, in some cases, understandable to human listeners. People who have lost the ability to speak after a disease can use their eyes or make other small movements to select on-screen letters just like what Stephen Hawking did, but that was extremely inconvenient. But if NN could re-create their speech directly, they might regain much more: for example, the ability to cut in a fast-moving conversation. The hurdles are high. “We are trying to work out the pattern of neurons that turn on and off at different time points, and infer the speech sounds,” says Nima Mesgarani, a computer scientist at Columbia University. “The mapping from one to the other is not straightforward at all.” How these signals translate to speech sounds varies from person to person, so computer models must be “trained” on each single patient. So you can imagine the work! The network of Mesgarani’s team analyzed data from five patients who heard recordings of stories and people naming numbers from zero to nine. The computer then reconstructed spoken numbers from neural data alone; when the computer “spoke” the numbers, a group of listeners named them with 75% accuracy. Neurosurgeon Edward Chang reconstructed entire sentences from brain activity caught from speech and motor areas while three patients raised their voice and read. In an online test, 166 people heard one of the sentences and had to select it from among 10 written choices. Some sentences were correctly identified more than 80% of the time. The researchers also pushed the model further: They used it to re-create sentences from data recorded while people silently mouthed words. “That’s an important result—one step closer to the speech prosthesis (假肢) that we all have in mind,” one of the researchers said. 12．What did researchers rely on to understand the patients’ speech better? A．Eye movements. B．On-screen letters. C．NN computer models. D．Patient-computer conversations. 13．What does the underlined part in Paragraph 3 mean? A．The job to build patients’ NN models is hard. B．Every patient has different speaking situations. C．Translating patients’ speech sounds is fruitful. D．It needs much time to learn computer models. 14．When did Edward Chang record the patients’ words? A．When they repeated the stories. B．When they counted numbers. C．When they mouthed words. D．When they spoke aloud. 15．In which section does the text appear most probably in a magazine? A．Figure. B．Lifestyle. C．Artificial Intelligence. D．Language Learning. 
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