Wearable Device Health Data: PTE Read Aloud Question with Sample Answers - Page 2
Your task
Look at the text below. In 30 seconds, you must read this text aloud as naturally and clearly as possible.
30 community answers with AI feedback
30 community answers with AI feedback
SCORE 14/15

AI Feedback
AI Feedback
Content:
48 words, 4 errors (8.33%): 4 replacements (device sentences → device sensors)
Oral Fluency:
Speech was smooth and fluent with no noticeable hesitations.
Pronunciation:
Pronunciation was clear and natural with no significant issues.
SCORE 14/15

AI Feedback
AI Feedback
Content:
The user omitted the word 's' in 'individual's health', and replaced 'containment' with 'contamination', resulting in 2 errors.
Oral Fluency:
The speech was fluent with a good pace and no disfluencies, indicating native-like fluency.
Pronunciation:
The pronunciation was clear and accurate, demonstrating a native-like quality.
SCORE 14/15

AI Feedback
AI Feedback
Content:
48 words, 4 errors (8.33%): 1 omission (variable → wearable), 3 replacements (aid → and, may → might, strains → strains of)
Oral Fluency:
The speech was smooth and natural with no noticeable hesitations.
Pronunciation:
The pronunciation was clear and accurate with no significant issues.
SCORE 14/15

AI Feedback
AI Feedback
Content:
48 words, 3 errors (6.25%): 2 replacements (abnormal fluctuations → abnormal situations), 1 omission (a → a).
Oral Fluency:
The speech was smooth and fluent with no noticeable hesitations.
Pronunciation:
Pronunciation was clear and natural with no significant issues.
SCORE 14/15

AI Feedback
AI Feedback
Content:
The user omitted the word 'the' before 'prevention', which counts as one error.
Oral Fluency:
The user demonstrated excellent fluency with no disfluencies and a smooth delivery.
Pronunciation:
The pronunciation was clear and accurate, with a high score indicating native-like performance.
SCORE 14/15

AI Feedback
AI Feedback
Content:
There were a few omissions and a minor error in the transcript, leading to a score of 4.
Oral Fluency:
Fluency was excellent with no disfluencies and a good speech rate.
Pronunciation:
Pronunciation was clear and accurate, demonstrating native-like qualities.
SCORE 14/15

AI Feedback
AI Feedback
Content:
The user made a minor error by using 'contamination' instead of 'containment', which counts as one error.
Oral Fluency:
The user maintained a smooth flow of speech with no disfluencies and an appropriate pace.
Pronunciation:
The user demonstrated excellent pronunciation with no significant errors.
SCORE 14/15

AI Feedback
AI Feedback
Content:
There were a few omissions and a slight rephrasing in the user's speech, specifically 'it is also thought' instead of 'it has also thought', leading to a minor deduction.
Oral Fluency:
The user demonstrated excellent fluency with no disfluencies and a good pace, achieving a perfect score.
Pronunciation:
The pronunciation was nearly perfect, with a high score indicating native-like articulation and clarity.
SCORE 14/15

AI Feedback
AI Feedback
Content:
48 words, 4 errors (8.33%): 1 omission (in → from), 2 replacements (source → device, aid → the), 1 mismatch (aid → aid)
Oral Fluency:
Speech was smooth with a natural rhythm and no noticeable hesitations.
Pronunciation:
Pronunciation was clear and native-like with minor errors.
SCORE 14/15

AI Feedback
AI Feedback
Content:
48 words, 5 errors (10.42%): 1 omission (a → missing), 1 replacement (devices → devices), 1 replacement (a → an), 1 replacement (individual's → individual's), 1 replacement (the → the)
Oral Fluency:
Speech was smooth and natural with a good rhythm.
Pronunciation:
Pronunciation was clear and articulate with no significant issues.
How to approach it
- Use the prep time. Scan the text and note difficult words before the mic opens.
- Read in phrases. Group words into meaningful chunks and pause at commas and full stops.
- Keep a steady pace. Do not rush. Clear pronunciation beats speed.
- Do not stop for mistakes. If you slip, keep going. Hesitation costs fluency marks.
Model Answer
a research study has concluded that physiological measurements taken from wearable device sensors might actually be able to indicate abnormal fluctuations relating to infections.