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166 Questions & Answers

Last Update: Sep 26, 2026

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Microsoft AI-901 Practice Test 38

Question 370

An interview transcription pipeline already requests speaker diarization, but its input mixer combines both microphones into one channel and the output tags every utterance as Speaker 1. Before replacing the recognition model, what should the engineer investigate?

  1. Remove all speaker timestamps so the output looks like one uninterrupted conversation.
  2. Generate a second synthetic voice for half the completed transcript and assume it identifies the original speaker.
  3. Infer speaker identity solely from the language name because both participants used the same spoken language.
  4. Inspect original channel/audio capture and diarization configuration, then compare attributed turns against labeled speech before declaring the model defective.

Explanation

Correct Answer

D:

The question identifies a capture mixer and configured diarizer, so investigate input layout and supported speaker-attribution settings first. Compare actual turn labels and overlap to separate a source/configuration fault from a model-quality fault.

Incorrect Answers

A:

Deleting temporal boundaries removes evidence needed to diagnose turn changes. It cannot repair a capture or diarization configuration problem.

B:

Playback synthesis creates artificial speech; it cannot recover which real person said each original sentence, especially after a mixed recording.

C:

A language label does not identify a speaker. Two people can use the same locale, so speaker-attribution evidence must come from the captured audio and the diarization workflow.

Question 371

A customer accessibility app produces a written ticket reply but needs to read it aloud through the Azure Speech SDK. Which component should be configured?

  1. A speech recognizer on the existing text as though it were microphone audio.
  2. Speaker diarization of the generated message.
  3. A speech synthesizer with a supported output voice and authorized Speech configuration.
  4. Configure recognition for the written ticket text and use its transcript result as the spoken reply, without a synthesizer.

Explanation

Correct Answer

C:

Configure the Speech synthesizer with a supported neural voice, language, authorized resource and playback output. Verify the returned audio rather than assuming text display equals speech completion.

Incorrect Answers

A:

A recognizer consumes acoustic input to produce text; feeding it existing reply text cannot produce the audible ticket response.

B:

Diarization distinguishes speakers in recorded audio and has no role in generating one reply from written content.

D:

Speech recognition consumes audio and returns text, the opposite of this requirement. Without a synthesis stage, no playable spoken ticket reply will be produced.

Question 372

A training tool should save spoken narration as an MP3 for later playback. The current code can synthesize text but discards the audio result. What must be added?

  1. Configure a supported audio output format and file/stream destination, then confirm synthesis completion.
  2. Use microphone recognition output as the MP3 content.
  3. Assume a successful text preview means the audio file was persisted.
  4. Store only the synthesis request and its text in persistent storage while discarding generated audio bytes, then label the record as MP3.

Explanation

Correct Answer

A:

Select a documented supported MP3 encoding and audio output destination, run synthesis, and confirm final success and actual file or stream bytes before reporting narration saved.

Incorrect Answers

B:

Recognition output is text derived from microphone audio, not MP3 bytes containing synthesized narration of the desired script.

C:

A successful text preview does not prove the speech synthesizer ran or wrote a durable file. Check returned audio status and storage outcome.

D:

A saved request can reproduce the text but is not a playable MP3. The client must select a supported audio format and persist actual completed synthesized audio.

Question 373

A speech guide already uses supported SSML `<break>` tags. When a hazard name from a database contains `R&D <high voltage>`, the speech request fails XML parsing instead of reading the warning. What should the application change?

  1. XML-escape dynamic hazard text (such as `&amp;`, `&lt;` and `&gt;`), keep the supported SSML elements valid and test the synthesized result.
  2. Remove the XML declaration and send the same unescaped `<high voltage>` string as an SSML element without validating it.
  3. Increase the recognizer phrase list to make the TTS service accept malformed SSML text.
  4. Treat the parsing error as successful synthesized audio and play an old unrelated warning clip.

Explanation

Correct Answer

A:

An ampersand and angle brackets are XML syntax characters; SSML text must use their entity forms. Escaping data preserves the intended hazard wording without accidentally inserting invalid tags or corrupting the supported break/voice structure.

Incorrect Answers

B:

Removing unrelated markup does not make raw ampersands or accidental tags valid XML text. An invalid element can still fail parsing or alter the intended spoken warning.

C:

Speech-recognition phrase lists concern matching incoming spoken words. They have no effect on whether a text-to-speech SSML document is well-formed XML.

D:

A parse error produces no validated new voice guidance for this hazard. Reusing a different warning would falsely associate unrelated safety instructions with the current instruction.

Question 374

A dental booking assistant recognizes "Tuesday the thirteenth" but its parsed date conflicts with the customer's confirmation screen. What should happen before booking?

  1. Select the next Tuesday automatically without asking if the date conflicts.
  2. Display or read back the interpreted date, resolve the ambiguity and validate the calendar transaction.
  3. Submit whichever parsed date appears first in the model text.
  4. Report the booking complete after producing a natural-language confirmation draft.

Explanation

Correct Answer

B:

Read back or display the precise interpreted date, resolve the contradiction with the user and check actual scheduling availability before creating a verified booking.

Incorrect Answers

A:

Choosing the next Tuesday can yield a different calendar date from the customer’s requested thirteenth and may book the wrong appointment.

C:

The first parsed candidate is not necessarily correct; ambiguous spoken dates need disambiguation rather than an arbitrary selection rule.

D:

A natural-language booking draft is not an appointment receipt. Confirmed date, consent and service acceptance are required before showing completion.

Question 375

A Speech transcription pipeline stores call recordings in a public debugging bucket while masking customer names only in the final report. What change is required?

  1. Protect source audio and transcript with least privilege, retention limits and sensitive-data masking where appropriate.
  2. Restrict who can read the finished transcript report but continue allowing all engineering staff to fetch raw call recordings for debugging.
  3. Assume downstream redaction automatically removes historical raw recording copies.
  4. Pseudonymize names in the transcript but leave the source recordings public because voice content is assumed not to contain direct identifiers.

Explanation

Correct Answer

A:

Protect original recordings and transcripts with least privilege, access logging and purpose-limited retention; redact unnecessary identifiers where appropriate. A masked downstream report does not secure upstream copies.

Incorrect Answers

B:

Access restrictions on the report do not apply automatically to the source audio. Debugging access still needs least privilege, traceability and retention controls appropriate to the sensitive recorded conversation.

C:

Downstream redaction changes only that output and cannot automatically erase historical audio stored elsewhere. Source storage needs its own governance.

D:

Audio can expose a voice, spoken identifiers and sensitive details even when the displayed transcript is masked. Source recordings need their own private storage, access policy and retention controls.

Question 376

A batch Azure Speech transcription job has reached its terminal Succeeded state. The client still has no searchable transcript because it has not downloaded the job’s result artifacts. What should it do next?

  1. Submit another transcription job under a new identifier and treat the second job as the missing result.
  2. Read the completed job’s documented result-file references, use authorized access to retrieve transcription artifacts and validate their completeness before indexing.
  3. Poll the succeeded job indefinitely without reading its output artifacts.
  4. Create a plausible transcript from the file name and mark it as the completed Speech response.

Explanation

Correct Answer

B:

Terminal success is an operation state, not the transcript itself. The client must fetch the output files with appropriate rights, check their contents and handle missing or incomplete artifacts before search ingestion.

Incorrect Answers

A:

A second job duplicates work and cannot retrieve the first completed transcript. The existing successful operation and its result artifacts should remain the authoritative source.

C:

Repeated polling is no longer the missing step once the job is terminal. It will not turn an inaccessible result location into parsed transcription data.

D:

A recording name contains no spoken-word evidence. Inventing a transcript after the operation succeeds would discard the actual recognition output and its timestamps.

Question 377

An Azure Speech text-to-speech app gets HTTP 429 responses for one standard neural voice even though its observed requests per second remain below its configured quota. A supported alternative voice succeeds in the same region. Select TWO useful investigation or mitigation steps.

  1. Request a larger text-to-speech transactions-per-second quota before checking whether the selected voice has limited capacity in its region.
  2. Compare the selected voice’s regional availability and backend-capacity behavior with a compatible supported voice.
  3. Use the same unavailable voice in the same region but increase its requested audio sample rate, assuming that more bandwidth provides extra voice capacity.
  4. Consider a suitable voice in its native region or an approved alternative voice while respecting the app’s language and data-location requirements.
  5. Double the parallel requests for the failing voice until its response throughput catches up, without checking provider capacity or retry limits.

Explanation

Correct Answers

B:

Compare the failing voice’s documented native-region availability and backend capacity with a compatible voice that succeeds. Quota headroom does not rule out voice-specific resource constraints.

D:

Where permitted, select a compatible available voice or its better-supported native region while preserving language, privacy and data-location requirements. Validate voice quality with actual workload samples.

Incorrect Answers

A:

Microsoft notes that many standard-voice 429 responses arise from per-voice regional backend capacity, not customer TPS quota. A quota increase alone may not fix this symptom.

C:

Sample rate affects audio encoding, not capacity of the selected voice’s backend in that region. Compare supported voices and locations before modifying unrelated synthesis settings.

E:

A backend capacity bottleneck is generally worsened by additional concurrent retries. Rate-aware handling and a supported voice/region choice are needed to avoid amplifying 429 failures.

Question 378

A portable field device must interpret voice instructions in a location with no network, but the selected recognition service requires cloud connectivity. What should the architecture plan?

  1. A documented supported offline/on-device alternative if available, or an honest unavailable state and deferred processing.
  2. Cache the cloud Speech endpoint URL and authentication token locally, then assume recognition requests can execute without any network path.
  3. Keep the recorded audio locally but display the transcript returned for the user's most recent successful online request.
  4. Queue microphone recordings for later upload, but immediately mark each transcription complete while the device is offline.

Explanation

Correct Answer

A:

If connectivity is unavailable, use a documented on-device/offline recognizer only when supported and appropriate. Otherwise report that recognition is deferred rather than claiming cloud transcription occurred.

Incorrect Answers

B:

Offline credentials or cached DNS still do not provide the remote speech-inference service. The device needs a supported local recognizer or must defer processing transparently.

C:

Reusing an older transcript can misattribute a command to the present recording. Offline capture may be queued, but unprocessed audio must not be represented as recognized speech.

D:

Queueing is a valid deferred transport technique, not proof that recognition has run. Status must remain pending until a supported engine processes the audio and returns the result.

Question 379

A Speech recognizer receives audio recorded at the wrong declared sample rate, yielding garbled transcription. What input check matters?

  1. Verify actual codec, channel count, sample rate and the SDK's supported audio input contract.
  2. Change only the file extension without converting samples.
  3. Assume a valid API key guarantees correct waveform interpretation.
  4. Increase model output tokens and leave the audio format invalid.

Explanation

Correct Answer

A:

Check actual media codec, channel layout and sample rate against the SDK’s input expectations. Incorrectly labeling samples can distort timing/pitch and corrupt recognition even with valid transport.

Incorrect Answers

B:

Renaming a file does not resample audio or change its encoded waveform. The parser still sees incompatible content.

C:

An API key authorizes access but has no bearing on whether a waveform’s actual sample rate or channels match the decoder.

D:

Generation token settings are irrelevant to the recognizer’s audio input format. Correct the capture or conversion pipeline first.

Question 380

A voice assistant reads confidential medical results aloud over a shared reception speaker. How should the application protect the user?

  1. Require appropriate identity, consent and private audio-delivery context before speaking protected results.
  2. Disable text display but continue unrestricted voice playback.
  3. Use a softer voice while keeping the same public speaker.
  4. Assume that because the patient requested results once, any nearby listener may hear them.

Explanation

Correct Answer

A:

Confirm the patient’s identity and permission, check whether the selected speaker is private, and use a consent-aware audio-delivery path before reading protected results aloud.

Incorrect Answers

B:

Hiding the text display does not stop people in the waiting area from hearing a shared speaker. Confidentiality includes audio channels.

C:

A softer voice may still be audible and leaves the same unauthorized listeners present. Volume is not an authorization mechanism.

D:

A prior request for results does not imply consent to broadcast medical details to everyone nearby. Verify the current delivery context.


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