AI Media Screenplay Assistant
Create Summaries, Synopses or EPGs in seconds
Overview
AI media screenplay assistant, a Generative AI based application focuses on analyzing the content of a screenplay into a concise and coherent summary. This AI tool uses LLM capabilities to comprehend the intricate narrative elements, including detailed understanding the character interactions, dialogue exchanges, and plot developments present in a screenplay. Common use cases include: generating summaries of movie screenplays, movie synopsis or EPGs for TV shows. This AI assistant reduces the time it takes to achieve high quality summarization task from days or hours to seconds, drastically improves productivity in media content production process. In essence, this AI screenplay assistant revolutionizes the way screenplays are evaluated and understood by providing concise, accurate, and informative summaries that capture the essence of complex narratives, ultimately facilitating more efficient and informed decision-making within the realm of filmmaking and storytelling.
Decypher the Golden Rule In Screenwriting
In the context of screenwriting, ‘Show, don’t tell’ is considered one of the golden rules in which story and characters are related through sensory details and actions rather than exposition. It fosters a more immersive writing style for the reader, allowing them to “be in the room” with the characters. Despite the benefits in capturing audiences’ attention, this particular writing style presents a major challenge for traditional tools to capture the essence of the stories in order to produce high quality summaries. Recent breakthrough in the field of NLP, Foundation Models have demonstrated remarkable capabilities in document understanding, and providing coherent and contextually relevant outputs. Applications that integrate with Foundation Models can dissect texts from screenplays, identifying key plot points, pivotal moments, character arcs, and thematic elements. By understanding the nuances of storytelling, the Foundation Model is capable of discerning the relationships between characters, deciphering their motivations, and recognizing the progression of the narrative structure. These capabilities have made Generative AI an excellent tool for generating high quality summaries, synopsis or EPGs for movies and shows.
Architecture
In general, LLMs work by taking the range of surrounding words into considerations to predict the next word. One major problem with LLMs when it comes to really long context is potential loss of coherence in long conversations or documents. Long context windows could result in out-of-context or irrelevant responses, such as losing the thread of the narrative, or forget key details when generating the subsequent texts. LLMs available today can only take in finite number of inputs. There are few which provide large window size like 100K, those models could be expensive to use, and could still suffer from long context problems such as ‘Lost In The Middle’. In this demo, we use Anthropic Claude v2 offered in Amazon Bedrock for the summarization task. However, providing an entire movie script to the model might exceed the limit of the model resulting in the model invocation errors. To design around this challenge, we break down the context into manageable chunks by limiting the number of tokens in each invocation context. In this demo, a given movie script is broken down into manageable, smaller and logical chunks based on the scenes in the script. Then each chunk (or the scene) is sent to the LLM to create fine grained summary. Finally, the chunk (or the scene) summaries are combined to form the context for the final coarse summary.
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