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AI Use Cases

A collection of over 250 uses for artificial intelligence

A continually updated list exploring how different types of AI are used across various industries and AI disciplines,including generative AI use cases, banking AI use cases, AI use cases in healthcare, AI use cases in government, AI use cases in insurance, and more

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Close captions for video

Introduction

Natural Language Processing (NLP) is a subfield of artificial intelligence (AI) that focuses on the interaction between computers and humans using natural language. The ultimate objective of NLP is to read, decipher, understand, and make sense of the human language in a valuable way. In the telecommunications industry, NLP AI is progressively being used to create closed captions for videos. This process involves the automatic conversion of spoken language into written text. Though initially introduced as a tool to aid the hearing impaired, closed captions are now widely used to better understand and engage with video content.

Challenges

Despite its potential, the use of NLP AI in closed captioning faces several challenges. Firstly, the accuracy of transcription is a substantial issue, with errors often occurring in converting spoken language into text. Secondly, the transcription process struggles with understanding context, slang, accents, and homonyms. It also has difficulty distinguishing between speakers, especially in noisy environments. Thirdly, the process is time-consuming and requires significant computational resources. Finally, the technology must comply with strict industry regulations and standards, such as those set by the Federal Communications Commission (FCC) in the United States.

AI Solutions

AI offers several solutions to these challenges. Firstly, advanced algorithms and deep learning models are increasingly improving the accuracy of transcriptions. For instance, Google's automatic speech recognition (ASR) technology, which utilizes deep neural networks, has made significant strides in this area. Secondly, AI can be used to understand context, slang, accents, and homonyms more effectively. Thirdly, AI can help automate the transcription process, making it more efficient and less resource-intensive. Finally, AI can help ensure compliance with industry regulations and standards by automatically checking for violations and errors.

Benefits

The use of NLP AI in closed captioning offers several benefits. Firstly, it improves the accessibility of video content for the hearing impaired. Secondly, it enhances the viewer's experience, especially in noisy environments or when the viewer prefers to watch without sound. Thirdly, it provides valuable metadata that can be used for search engine optimization (SEO) and content discovery. Finally, it enables real-time transcriptions, which are crucial for live events and broadcasts.

Return on Investment

The return on investment (ROI) for using NLP AI in closed captioning is substantial. It not only increases viewer engagement and satisfaction, but also drives more traffic to video content through improved SEO. Moreover, it reduces the costs associated with manual transcription and the potential fines for non-compliance with industry regulations. For instance, Verizon, a telecommunications company, has reported significant savings and improved viewer satisfaction since implementing AI-powered closed captioning.

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