雅思阅读 038 · Can AI Hear Schizophrenia?

改编自 Scientific American（Astrid Landon & Knowable Magazine, 2026）。题型：选择题 + T/F/NG + 填空。难度：较难（Passage 3，约 900 词）。

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🎧 课文朗读音频（约 1 分钟）

正文 Passage

Schizophrenia is tough to diagnose. Patients may present with hallucinations (sometimes), social withdrawal (maybe) or delusions (not always). More generally, they just sound unlike themselves. Clinicians rely on their expertise and subtle cues to determine how different patients' speech is, along with which symptoms appear over time, to justify leaning toward schizophrenia rather than another mental illness. This leads to delays in diagnosis. Americans with psychotic disorders — more than 3 million of whom have schizophrenia — receive a diagnosis a year and a half, on average, after their first symptoms appear.

Researchers are now investigating whether artificial intelligence could improve diagnosis and care by listening to and analysing what clinicians can't hear or quantify, even if the software is working off just a few minutes of conversation.

"We have the tools to do that with the kind of precision that we have never had before," says Thomas Insel, a psychiatrist and neuroscientist who led the US National Institute of Mental Health for 13 years.

Schizophrenia is a disorder that interferes with people's perception of reality, their thinking and their emotional regulation. It affects about 23 million people worldwide and is usually diagnosed between the late teens and early 30s. No one knows what causes it, but research suggests it could be a combination of genetics, environment, brain chemistry and substance use.

Clinicians stress the importance of detecting the disorder as early as possible, because the longer it is left untreated, the poorer the response to treatment and the greater the risk of brain tissue loss, worsening symptoms and suicide.

Part of the problem is that diagnosis currently depends on subjective assessments. Based on what a patient says and how they say it, clinicians fill out one of several different rating scales to rank the severity of symptoms and arrive at a diagnosis. But the process is difficult to standardise, and clinicians' scores for a given patient can differ by 30 to 50 percent.

Artificial intelligence could help to automate the process, making diagnosis both speedier and more accurate.

Psychiatrists view speech as a solid marker to evaluate someone's mental state since it can indicate disordered thinking, a hallmark of schizophrenia. People with disordered thought tend to move erratically from idea to idea — a chaotic path that AI could help to identify.

A team of researchers in the Netherlands wondered whether AI could help. They selected audio recordings of people who had previously been diagnosed with schizophrenia by psychiatrists, then used software to measure 88 features, such as loudness, length of pauses, vowel pronunciation and intonation. They then used these measures to train an AI program to distinguish people with and without schizophrenia.

When the team tested their AI using audio files from new patients it had not heard before, it differentiated schizophrenic patients from healthy controls with 86.2 percent accuracy and could even distinguish between different subtypes of the illness.

The approach isn't especially useful for the clearest cases, says study coauthor Alban Voppel. But AI could help to detect patients in early stages or at high risk of becoming schizophrenic, and to predict relapse.

Sunny Tang, a psychiatrist and researcher at the Feinstein Institutes for Medical Research near New York City, took a different approach. Instead of studying the sounds of speech, her team looked at its content. They built a type of AI called a machine learning model to assign a mathematical address to each word in a transcript of a patient's conversation. By looking at the constellation of addresses, Tang's program can tell whether a sentence stays in the same general neighbourhood or leaves town and returns again, indicating disorganised thinking.

When Tang provided transcripts of speech by people with and without schizophrenia, she found that the AI could distinguish the two groups with 87 percent accuracy. Clinical raters, who assessed patients without the AI, were only 68 percent accurate.

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题目 Questions

Questions 1-4: Choose the correct letter.

1. How long on average does it take to diagnose schizophrenia after first symptoms?

• A. six months
• B. one year
• C. a year and a half
• D. three years

2. How many people worldwide are affected by schizophrenia?

• A. about 3 million
• B. about 13 million
• C. about 23 million
• D. about 33 million

3. What accuracy did the Dutch AI achieve when testing new patients?

• A. 68 percent
• B. 86.2 percent
• C. 87 percent
• D. 95 percent

4. Sunny Tang's approach focused on:

• A. the sounds of speech
• B. the content of speech
• C. facial expressions
• D. brain scans

Questions 5-8: T/F/NG

5. Schizophrenia is usually diagnosed between the ages of 40 and 50.

6. Clinicians' scores for a given patient can differ by 30 to 50 percent.

7. The Dutch AI could distinguish between different subtypes of schizophrenia.

8. Clinical raters without AI were more accurate than the AI model.

Questions 9-13: Complete the notes. Choose NO MORE THAN TWO WORDS.

• The Dutch AI measured (9) ____________ features such as loudness and pauses.
• Schizophrenia usually diagnosed between the late teens and early (10) ____________.
• The longer schizophrenia is left untreated, the poorer the response to (11) ____________.
• Tang's AI assigned a mathematical (12) ____________ to each word.
• Clinical raters without AI were only (13) ____________ percent accurate.

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答案 Answers

题号	答案
1	C
2	C
3	B
4	B
5	FALSE (late teens to early 30s)
6	TRUE
7	TRUE
8	FALSE (clinical raters only 68%)
9	88
10	30s
11	treatment
12	address
13	68

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核心词汇

schizophrenia / diagnosis / psychiatrist / artificial intelligence / speech / hallucination / delusion / disordered thinking / machine learning / accuracy / relapse