Self-study
Columnist: Support Computer voice-recognition technology currently cannot distinguish between homophones such as "their" and "there." As a consequence, Conclusion until voice-recognition technology is improved to recognize and utilize grammatical and semantic relations among words, voice-recognition programs will not accurately translate a computer user's spoken words into written text.
What's the Argument?
The columnist observes that voice-recognition technology can't tell homophones apart (words that sound the same but are spelled differently, like "their" and "there"). From this, she concludes that voice-recognition programs won't be able to translate spoken words into written text accurately until the technology is improved to recognize grammatical and semantic relations among words.
Note that by using the word "until," the columnist is saying that recognizing grammar and semantics is necessary for accurate translation. Not that it would be enough on its own, but that without it, accurate translation isn't happening.
The Missing Link
Let's start by identifying the premise and conclusion separately. Notice that the conclusion below is expressed as "can't recognize grammar/semantics → can't translate accurately" rather than "translate accurately → recognize grammar/semantics." These mean the same thing. The form below makes it easier to see how the premise connects to the conclusion through a chain.
Premise:
can't distinguish homophones
Conclusion:
can't recognize grammar/semantics
→
can't translate accurately
How does the premise connect to the conclusion? Through a chain. Here's the full chain the columnist needs:
can't recognize
grammar/semantics
→
grammar/semantics
can't distinguish
homophones
→
homophones
can't translate
accurately
accurately
missing — the assumption
implied by premise ✓
Right side of the chain (implied by premise)
The premise tells us the tech can't distinguish homophones. Although it doesn't spell out the consequence, it's implied: if the tech can't tell "their" from "there," it will get some words wrong, so it can't translate accurately. In other words, distinguishing homophones is a requirement for accurate translation.
Left side of the chain (missing — the assumption)
The columnist never explains why distinguishing homophones requires recognizing grammar and semantics. She just jumps from the homophone problem to grammar/semantics as the solution. Maybe the tech could distinguish homophones some other way, like analyzing word-frequency patterns. The correct answer should establish that grammar/semantics recognition is necessary for solving the homophone problem.
Analysis by Kevin_Lin
13.
Which one of the following ██ ██ ██████████ ████████ ██ ███ ███████████ █████████
a
In order for ████████ █████████████████ ██████████ ██ ███████████ ███████ ███████████ ██ ████ ██ ████ ██ █████████ ███████████ ███ ████████ █████████ █████ ██████
b
If voice-recognition technology ██ ████████ ██ █████████ ███ ███████ ███████████ ███ ████████ █████████ █████ ██████ █████████████████ ████████ ████ ██████████ █████████ ██████ █████ ████ █████
c
Humans can distinguish ███████ ██████████ ███████ █████ ███████████ █████ ███ ███████████ ███ ████████ █████████ █████ ██████
d
Unless voice-recognition technology ███ ███████████ ███████ █████ ████ ███ ███████████ ██ ██████ █████████ ███████████ ███ ████████ █████████ █████ ██████
e
Computer programs that █████ ███ ████████ ███ ███████ ██ ███████ ████ ███ █████████ ████ ██ ███████████ ███████ ███████████