A side-by-side recording from the same farmer can show whether Ghanaian English crop terms preserve, distort, or remove the meaning AgriVoice needs before it selects a reviewed answer. The test should compare the meaning captured from a pure Asante Twi question with the same question spoken the way a farmer may naturally mix Twi and crop words such as “fungicide” or “COCOBOD.”
At 6:40 in the morning, Kofi stands beside a cocoa tree in an illustrative field scene, his phone held close to his mouth and three marked pods in his other hand. He has noticed the marks spreading along one branch, and he wants to know what to do before deciding whether to buy and apply a product. A wrong interpretation could send him toward the wrong reviewed guidance. A missing interpretation could leave him with no answer while the problem continues.
He records the first version in Asante Twi. Then he records the same question again, using the crop term he would normally say in Ghanaian English. The difference may be one word. That one word can decide whether the system identifies the same problem, chooses a different reviewed content block, or escalates safely because it cannot tell.
Record the same meaning twice
The recording pair should begin with one real farmer question, spoken twice by the same person in the same setting. Keep the intended meaning stable. Change only the language mix.
For example, the first recording might use a Twi term throughout. The second may retain the Twi sentence structure while using the English crop term the farmer would use in ordinary conversation. The goal is to observe meaning before any answer is delivered.
This matters because farmers do not speak in tidy language categories. A question may move between Asante Twi and Ghanaian English within a single sentence, especially around product names, diseases, organisations, measurements, and farming terms. Treating those words as noise risks losing the part of the question that carries the decision.
The paired recording should go through the same speech recognition and block-selection path. Reviewers can then compare the transcript, the selected block or blocks, the confidence, and the escalation outcome. If the pure-Twi version reaches a reviewed disease-identification block while the mixed version reaches a pesticide block, the test has found a safety issue worth investigating before farmer exposure.
Kofi’s two recordings may sound almost identical to him. The system has to prove that it hears the same request.
Meaning comes before a spoken response
AgriVoice is designed to select from reviewed content blocks. It does not generate new agronomy advice from scratch. That boundary matters most when a question concerns pesticides, dosage, re-entry, or harvest timing.
A transcription error can therefore create two different risks. It may select a block that does not fit the farmer’s problem. Or it may fail to recognise enough of the question and should escalate to a named extension officer rather than guess.
The second outcome is often the safer one. Three chemical blocks remain withheld because dosage, re-entry, and pre-harvest details still need Ghanaian agronomist review. A mixed-language recording that pushes an uncertain question into one of those areas should produce a clear safe next step, not an authoritative-sounding answer. The stakes behind that choice are explored in The Three Withheld Chemical Blocks, and What an Unreviewed Dose Could Cost.
The test is not a contest between “correct” Twi and “incorrect” English. It asks a narrower operational question: does the system retain the meaning a farmer intended when their everyday speech includes both?
Compare the points where meaning can shift
A useful review sheet can place the two recordings side by side and record a few concrete observations:
- Did the speech recogniser capture the crop term, or replace it with a different word?
- Did both recordings lead to the same reviewed block selection?
- Did either version add an unsafe extra block?
- Did the system escalate when the intended meaning stayed unclear?
- Did a reviewer agree that the selected content answered the farmer’s actual question?
The comparison needs human review from a Twi-speaking agriculture reviewer. A transcript can look plausible while changing the domain noun that determines the advice. Neuralis has already seen machine translation turn `kokoo`, meaning cocoa, into “chicken.” Fluent output gave no warning that the meaning had changed.
That is why the recording should preserve the original audio alongside the transcript. A reviewer needs to hear what Kofi said, see what the system captured, and judge the selected response path against the actual question.
Build the field set from natural speech
The current evaluation plan calls for about 40 real Twi farmer questions across common, ambiguous, pesticide, out-of-domain, code-switched, ASR-corrupted, and multi-block cases. Same-farmer paired recordings can make the code-switched portion more precise.
Start with questions where the crop term is central. Disease descriptions, product names, spray timing, quantities, and references to COCOBOD are useful candidates because a substitution can change the next action. Avoid rehearsed scripts that make every speaker sound alike. The useful recording is the one a farmer would send when they are concerned about a real plant in front of them.
By the time Kofi leaves the tree, the pods still need attention. What has changed is the test around his question: the team can see whether one English crop term carried the same meaning through the system, or whether it triggered a safer escalation before any reviewed block was spoken aloud.
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