You are developing the knowledgebase. You use Azure Video Analyzer for Media (previously Video indexer) to obtain transcripts of webinars. You need to ensure that the solution meets the knowledgebase requirements. What should you do?
A.
Create a custom language model
B.
Configure audio indexing for videos only
C.
Enable multi-language detection for videos
D.
Build a custom Person model for webinar presenters
A is the answer.
https://learn.microsoft.com/en-us/azure/azure-video-indexer/customize-language-model-overview
Azure Video Indexer supports automatic speech recognition through integration with the Microsoft Custom Speech Service. You can customize the Language model by uploading adaptation text, namely text from the domain whose vocabulary you'd like the engine to adapt to. Once you train your model, new words appearing in the adaptation text will be recognized, assuming default pronunciation, and the Language model will learn new probable sequences of words.
the correct choice between Stream and string depends on the source of the image:
If you have the image file and want to upload it directly from the client or server where the request is being made, you should use a Stream. This approach is direct and efficient for handling binary data without the need for encoding or hosting the image externally.
If the image is already hosted online and accessible via a URL, you use a string containing the URL to let the API fetch the image for analysis.
Create a custom language model is CORRECT because this feature ensures that the solution can transcribe accounting jargon with high accuracy. This directly aligns with the knowledgebase requirement to support transcription of specialized terminology, such as accounting-specific jargon, which cannot be achieved with generic models or basic audio indexing. A custom language model allows training on domain-specific terminology, improving transcription quality.
A is correct
A. Create a custom language model: This option allows for the customization of the language model used for transcribing audio and video content. By creating a custom language model, you can train it to understand and transcribe specialized jargon and industry-specific terminology with high accuracy. This directly addresses the requirement to transcribe jargon with high accuracy and supports searches for equivalent terms by ensuring that the transcriptions are as accurate and relevant as possible.
--- Can transcribe jargon with high accuracy
Video Indexer (VI), the AI service for Azure Media Services enables the customization of language models by allowing customers to upload examples of sentences or words belonging to the vocabulary of their specific use case. Since speech recognition can sometimes be tricky, VI enables you to train and adapt the models for your specific domain. Harnessing this capability allows organizations to improve the accuracy of the Video Indexer generated transcriptions in their accounts.
https://azure.microsoft.com/en-us/blog/new-ways-to-train-custom-language-models-effortlessly/
Leaning towards A on this.
https://azure.microsoft.com/en-us/blog/new-ways-to-train-custom-language-models-effortlessly/
https://docs.microsoft.com/en-us/azure/azure-video-indexer/video-indexer-overview
I think you're right
https://azure.microsoft.com/en-us/blog/new-ways-to-train-custom-language-models-effortlessly/
upvoted 2 times
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