Detecting User Questions in Video Streams
Answer
Correct answer: A — Speech-to-text in the Azure AI Speech service converts the user's spoken words into text to detect questions.
You are building an internet-based training solution. The solution requires that a user's camera and microphone remain enabled. You need to monitor a video stream of the user and detect when the user asks an instructor a question. The solution must minimize development effort. What should you include in the solution?
Community Votes
100% of anonymous learners picked answer A. Votes are pick records left by other test-takers — they are not the verified answer.
Community Insight
The trap is focusing on video (Vision) when the trigger is a spoken question, which requires Audio processing (Speech).
This question tests the integration of Azure AI services for real-time monitoring. The correct solution leverages speech-to-text to convert audio input into text for question detection.
Candidates often choose Face service or Object Detection because the scenario mentions a 'video stream', ignoring that the specific event to detect is verbal.
Community Discussion (16 comments)
syupwsh
👍 1
Selected: A
speech-to-text in the Azure AI Speech service is designed to convert spoken language into text, which is essential for detecting when a user asks a question during a video stream. This service can process the audio captured by the user's microphone, transcribe the spoken words in real-time, and allow the system to recognize when a question is being asked with minimal development effort. A for answer
MostafaAbdellahAhmed
👍 3
A. Speech-to-text in the Azure AI Speech service Explanation: Speech-to-Text in the Azure AI Speech service can transcribe spoken language into text in real time, enabling the detection of questions when users speak. This approach minimizes development effort by directly converting speech to text, allowing easy identification of questions.
SAMBIT
👍 1
Definitely its not A. That's a bunker
HaraTadahisa
👍 1
Selected: A
A is correct answer.
Belicova
👍 4
Go with D From Copilot: To monitor a video stream of the user and detect when the user asks an instructor a question while minimizing development effort, consider using object detection. Specifically, you can leverage existing models or frameworks (such as YOLOv3) to detect people in real-time from the video stream1. Once you identify a person asking a question, you can trigger further actions or alerts. This approach avoids the complexity of speech-to-text or language detection and focuses on the specific task at hand. Therefore, go with D. object detection in Azure AI Custom Vision!
anto69
👍 1
Selected: A
To minimize effort: A is enough
reiwanotora
👍 2
Selected: A
user's camera and microphone remain enabled, so A is right.
anntv252
👍 1
Selected: A
Because user's camera and microphone remain enabled. Azure AI Speech service is recommend for using
Barry123456
👍 2
It says video stream. It doesn't say the video stream has audio. I deal with video only streams all day. Don't assume.
sivapolam90
👍 1
Selected: A
A. speech-to-text in the Azure AI Speech service
Murtuza
👍 2
Selected: A
The best option for this scenario would be A. speech-to-text in the Azure AI Speech service. This service can transcribe the user’s spoken words into written text, which can then be analyzed to detect when a question is being asked. This would be more efficient and direct for detecting questions in a video stream, compared to the other options which focus on language detection, face recognition, and object detection. These other services might not be as effective for this specific use-case.
NullVoider_0
👍 1
Selected: A
A. speech-to-text in the Azure AI Speech service This service can transcribe the spoken words into text in real-time, which can then be analyzed to detect questions. It’s an efficient way to monitor for specific verbal cues or keywords that indicate a question is being asked, without the need for extensive programming or manual review. This approach minimizes development effort while providing a robust solution for the requirement.
Murtuza
👍 3
The correct CHOICE is C. I made a silly typo but my explanations are right on point.
Murtuza
👍 3
The other options are not directly relevant to detecting user questions in a video stream: Speech-to-text (Option A): Converts spoken language into text. While useful for transcribing audio, it doesn’t directly address identifying user questions. Language detection (Option B): Determines the language of text. It’s not specifically designed for monitoring video streams or detecting questions. Object detection (Option D): Identifies objects within images, but it’s not suitable for detecting user interactions or questions. Therefore, Option C (the Face service in Azure AI Vision) is the most appropriate choice for your scenario.
Mehe323
👍 4
The user can talk, but it doesn't have to be a question. I think the focus should be on detecting whether something is a question or not and for that, you need speech to text first. Face doesn't make sense as identifying questions is not the purpose of that service: 'The Azure AI Face service provides AI algorithms that detect, recognize, and analyze human faces in images. Facial recognition software is important in many different scenarios, such as identification, touchless access control, and face blurring for privacy.' https://learn.microsoft.com/en-us/azure/ai-services/computer-vision/overview-identity
chandiochan
👍 2
Selected: A
speech-to-text in the Azure AI Speech service/ This service can transcribe spoken words into written text in real-time, allowing you to monitor the audio for specific triggers, like questions, which can then be further processed or flagged for response. This solution is efficient and requires minimal development effort for integrating audio streaming and speech recognition capabilities.
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Expert Analysis
Why the Answer Is Correct
Correct answer: A — Speech-to-text in the Azure AI Speech service. The core requirement is to detect when a user asks a question. Since asking a question is a verbal act, the most direct and minimally developed solution is to transcribe the audio from the microphone into text using Azure AI Speech. This allows simple NLP rules or intent recognition to identify questions without complex vision models.Why the Other Options Are Wrong
Option B (Language Detection) only identifies the language, not the content or intent. Option C (Face Service) analyzes facial attributes like emotion or gender, not verbal queries. Option D (Custom Vision) is for image classification or object detection, which cannot process the semantic content of a spoken question. While the input is a video stream, the critical data point is the audio track.Community Comment Notes
Community consensus strongly favors A, with votes at 100%. Commenters note that since the camera and microphone are enabled, speech-to-text is the logical choice for detecting verbal questions. One commenter correctly points out that Face service does not make sense for identifying questions as it lacks audio processing capabilities.Official Reference
Exam Strategy
Always map the 'action' or 'event' you need to detect to the specific modality (Audio, Visual, Text). If the trigger is spoken, use Speech services; if it is visual behavior, use Vision services.
Frequently Asked Questions
Why not use Face Service to detect mouth movement?
Face Service detects facial landmarks and attributes, not semantic intent like 'asking a question'. It cannot distinguish between talking and asking.
Does the video stream require Azure AI Vision?
No. While the input is video, the task is audio-based. Using Speech-to-text minimizes development effort by leveraging existing transcription APIs.