{"schema_version":"1.0","canonical_url":"https://patentable.app/patents/US-9854202","patent":{"patent_number":"US-9854202","title":"Processing segments of closed-caption text using external sources","assignee":null,"inventors":[],"filing_date":"2014-12-11T00:00:00.000Z","publication_date":"2017-12-26T00:00:00.000Z","cpc_codes":["H04N","G06F","H04N","H04N","H04N","H04N","H04N"],"num_claims":20,"abstract":"Particular embodiments provide supplemental content that may be related to video content that a user is watching. A segment of closed-caption text from closed-captions for the video content is determined. A first set of information from the segment of closed-caption text, such as terms may be extracted. Particular embodiments use an external source that can be determined from a set of external sources. To determine the supplemental content, particular embodiments may extract a second set of information from the external source. Because the external source may be more robust and include more text than the segment of closed-caption text, the second set of information may include terms that better represent the segment of closed-caption text. Particular embodiments thus use the second set of information to determine supplemental content for the video content, and can provide the supplemental content to a user watching the video content."},"analysis":{"summary":"The Processing Segments of Closed-caption Text Using External Sources patent introduces a novel system for enhancing video content by dynamically linking closed captions to external knowledge sources. The core innovation lies in its ability to automatically extract key terms from closed-caption text and use these terms to query external databases, knowledge graphs, and other online resources. This solves the problem of limited context and depth in traditional closed-captioning, providing viewers with richer, more informative content.\n\nThe system employs natural language processing (NLP) techniques to identify relevant terms in the captions. These terms are then used to search a curated database of external sources, such as Wikipedia, news articles, and academic journals. The resulting information is presented to the viewer as supplemental content, enhancing their understanding and engagement. This approach offers significant business value by increasing user engagement on video platforms, improving accessibility for viewers with disabilities, and creating new opportunities for targeted advertising and monetization.\n\nThe market opportunity for this technology is substantial, given the growing demand for video content and the increasing importance of accessibility. Video streaming platforms, educational institutions, and broadcasters can all benefit from implementing this system. By providing viewers with a more immersive and informative experience, this technology has the potential to transform the way we consume and interact with video content.\n\nThis innovation presents a significant step forward in making video content more accessible, engaging, and informative. As video continues to dominate our lives, technologies like this will become increasingly important in shaping the way we consume and interact with information. The Processing Segments of Closed-caption Text Using External Sources patent has the potential to revolutionize video accessibility and content enhancement, providing viewers with a richer, more engaging, and more informative experience.","layman_explanation":"The Processing Segments of Closed-caption Text Using External Sources patent addresses a common problem with video content: closed captions, while helpful for accessibility, often lack the context and depth needed for full comprehension. This patent presents a solution that enhances the viewing experience by linking closed captions to external sources of information.\n\n**1. What Problem Does This Solve?**\n\nImagine watching a documentary about a historical event. The closed captions provide a transcription of the spoken words, but they don't offer any additional context or background information. You might hear a reference to a specific person or event that you're not familiar with, leaving you feeling lost. Existing closed-captioning systems fall short because they only focus on transcribing speech, neglecting the need for supplemental information.\n\n**2. How Does It Work?**\n\nThis patent describes a system that analyzes the closed captions in real-time and identifies key terms and concepts. Think of it like a smart search engine that works alongside your video player. When the system detects a word or phrase that might benefit from further explanation, it automatically searches external sources like Wikipedia, online dictionaries, or news articles. The resulting information is then presented to you in a non-intrusive way, such as a pop-up window or a side panel. This allows you to quickly learn more about the topic without interrupting your viewing experience. It's like having a built-in research assistant that provides you with instant access to relevant information.\n\n**3. Why Does This Matter?**\n\nThe market impact of this technology is significant. Video streaming platforms can use it to increase user engagement and satisfaction. Educational institutions can use it to create more immersive and effective learning experiences. Broadcasters can use it to provide viewers with a deeper understanding of current events. The competitive advantages are clear: this technology provides a richer, more informative viewing experience than traditional closed-captioning systems. This can lead to increased user loyalty, higher subscription rates, and new revenue opportunities. The potential ROI is high, as this technology can enhance the value of video content and attract a wider audience.\n\n**4. What's Next?**\n\nFuture applications of this technology could include personalized learning experiences, where the system tailors the supplemental content to the individual viewer's knowledge and interests. We can expect to see wider market adoption as video continues to dominate our lives and as the demand for accessible and informative content grows. This technology has the potential to transform the way we consume and interact with video, making it more engaging, informative, and accessible for everyone. Investment in this area will likely focus on improving the accuracy and efficiency of the system, expanding the range of external sources, and developing new user interfaces.","technical_analysis":"The Processing Segments of Closed-caption Text Using External Sources patent details a system that significantly enhances video content through the intelligent use of closed captions and external data sources. The technical architecture revolves around several key components working in concert.\n\nFirst, a text extraction module processes the closed-caption stream in real-time. This module uses Optical Character Recognition (OCR) if the captions are embedded as images or directly parses the text if available in a standard format. The extracted text is then segmented into meaningful phrases or sentences.\n\nNext, a natural language processing (NLP) engine analyzes these segments. This engine performs tasks like part-of-speech tagging, named entity recognition, and keyword extraction. The goal is to identify the most relevant terms and concepts within the caption text. Algorithms like TF-IDF (Term Frequency-Inverse Document Frequency) might be employed to weight terms based on their importance and frequency.\n\nOnce key terms are identified, a query generation module formulates search queries for external data sources. This module might use techniques like query expansion to broaden the search and increase the likelihood of finding relevant information. The patent specifies the use of various external sources, including Wikipedia, news articles, and specialized databases.\n\nThe results from these external sources are then filtered and ranked based on relevance. Algorithms that consider factors like the source's authority, the match between the query and the result, and the user's preferences might be employed.\n\nFinally, a presentation module integrates the supplemental information into the video playback. This might involve displaying the information in a side panel, overlaying it on the video, or providing interactive annotations. The user interface is designed to be non-intrusive and easy to use.\n\nIntegration with existing video players can be achieved through APIs or plugins. The system can be implemented as a cloud-based service or as a local application. Performance characteristics depend on factors like the speed of the NLP engine, the latency of the external data sources, and the bandwidth of the network connection. Code-level implications involve careful attention to data structures, algorithms, and communication protocols to ensure efficient and reliable operation.\n\nThis patent represents a significant advancement in video technology, offering a powerful way to enhance the viewing experience and improve accessibility. Further research and development could focus on improving the accuracy of the NLP engine, expanding the range of external data sources, and optimizing the user interface.","business_analysis":"The Processing Segments of Closed-caption Text Using External Sources patent presents a compelling business opportunity with significant market potential. The core value proposition lies in enhancing the video viewing experience, making it more engaging, informative, and accessible. This has implications for various industries, including entertainment, education, and news media.\n\nThe market opportunity is substantial. The global video streaming market is experiencing rapid growth, driven by increasing internet penetration, the proliferation of mobile devices, and the rising demand for on-demand content. As video consumption continues to increase, the need for enhanced viewing experiences will become even more critical. The Processing Segments of Closed-caption Text Using External Sources patent addresses this need by providing a more immersive and informative viewing experience.\n\nThe competitive advantages of this technology are clear. Traditional closed-captioning systems simply transcribe the audio, lacking the context and depth required for a comprehensive understanding. The Processing Segments of Closed-caption Text Using External Sources patent overcomes these limitations by dynamically linking closed captions to external knowledge sources. This provides viewers with richer, more relevant information, enhancing their engagement and comprehension.\n\nRevenue potential can be realized through various business models. Video streaming platforms could offer this technology as a premium feature, charging users a subscription fee for access. Educational institutions could integrate this technology into their online learning platforms, improving student engagement and outcomes. Broadcasters could use this technology to provide viewers with a deeper understanding of current events.\n\nStrategic positioning is crucial. Companies implementing this technology should focus on building partnerships with content providers, technology vendors, and educational institutions. This will help to accelerate adoption and expand the market reach. ROI projections are highly dependent on the specific business model and market conditions. However, given the substantial market opportunity and the clear competitive advantages, the potential for a high ROI is significant.\n\nThis technology has the potential to disrupt the video industry, creating new opportunities for innovation and growth. Companies that embrace this technology will be well-positioned to capitalize on the growing demand for enhanced video experiences.","faqs":null,"topics":[],"tech_cluster":null},"seo":{"title":"Processing segments of closed-caption text using external sources","description":"Particular embodiments provide supplemental content that may be related to video content that a user is watching. A segment of closed-caption text from closed-captions for the video content is determi","keywords":[]},"attribution":{"source":"Patentable","source_url":"https://patentable.app","canonical_url":"https://patentable.app/patents/US-9854202","license":"CC-BY-4.0-like","license_terms":"AI-generated analysis on this page (summary, layman_explanation, technical_analysis, business_analysis, faqs) may be reused with attribution and a visible link back to the canonical URL above. Patent abstracts, claims, and bibliographic data are USPTO public domain.","required_link":"https://patentable.app/patents/US-9854202","citation_suggestion":"Patentable. \"Processing segments of closed-caption text using external sources\" (US-9854202). https://patentable.app/patents/US-9854202","copyright_holder":"Nomic Interactive Technology LLC"},"links":{"html":"https://patentable.app/patents/US-9854202","json":"https://patentable.app/api/llm-context/US-9854202","site":"https://patentable.app","llms_txt":"https://patentable.app/llms.txt"},"generated_at":"2026-05-31T09:20:19.812Z"}