You are building an app that will use the Azure Video Indexer service. You plan to train a language model to recognize industry-specific terms. You need to upload a file that contains the industry-specific terms. Which file format should you use?

To train a custom language model in Azure Video Indexer with industry-specific terms, you must provide the data as a text file (.txt). The service expects a simple list where each term or phrase is on a new line. This file is then used as training data to improve the accuracy of the speech-to-text transcription for your specific domain's vocabulary. The text file must be encoded as UTF-8 BOM.

A. PDF: This is a document format not supported for uploading vocabulary lists for language model customization in Video Indexer.

B. XML: This structured data format is not the specified format for providing a simple list of terms for language model training.

D. XLS: This spreadsheet format is not supported for this purpose; Video Indexer requires a plain text file for vocabulary lists.

1. Microsoft Learn. (2023). Customize a language model in Azure AI Video Indexer. In the "Upload training data" section, step 2 states, "Browse for a text file. You can upload a text file with a list of domain-specific words. Each word should be in its own line."

Reference: https://learn.microsoft.com/en-us/azure/azure-video-indexer/customize-language-model-with-api#upload-training-data

2. Microsoft Learn. (2023). Create a training data set to customize a language model. This document further clarifies the requirements: "Gather all the text files that contain domain-specific vocabulary... The files should be in UTF-8 BOM format."

Reference: https://learn.microsoft.com/en-us/azure/azure-video-indexer/create-training-data-set-for-language-model