Video Script Generation Through Human-Body and Voiceprint Matching
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing methods for generating video scripts fail to accurately identify characters in videos due to the omission of character introduction content and inadequate consideration of both human body and voiceprint features, leading to incomplete script summaries and recognition errors.
Innovation Solution
A method that extracts both human body and voiceprint features from speech segments in a video, matches these features with a character library, and generates a script based on the identified characters and dialogue text, ensuring comprehensive character identification and accurate script generation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If only speech recognition is used to generate video scripts, then the generation process is simple and fast, but character identification accuracy is poor and scripts are incomplete
Solution Approach 1:
The patent combines multiple feature extraction methods (human body features from video frames, voiceprint features from speech segments, and text features from speech recognition) into a unified character identification system. This merging of multiple identification approaches resolves the contradiction by maintaining fast processing while significantly improving character identification accuracy through multi-dimensional feature matching against the character library.
Solution Approach 2:
The patent segments the character identification process into distinct feature extraction stages: human body feature extraction from video frames, voiceprint feature extraction from speech segments, and text feature extraction from speech recognition. This segmentation allows each feature type to be processed independently and efficiently, maintaining productivity while enabling comprehensive character identification that improves accuracy.
2Device complexity
If character identification is omitted to simplify the process, then processing is faster, but script completeness and accuracy deteriorate
Solution Approach 1:
The patent performs preliminary character identification by extracting human body features and voiceprint features before script generation. This preliminary action ensures characters are accurately identified and matched with the character library in advance, preventing information loss about character introductions while keeping the subsequent script generation process efficient and relatively simple.
Solution Approach 2:
The patent introduces a character library as an intermediary component that stores pre-defined character information. The extracted features (human body, voiceprint, text) are matched against this intermediary character library to identify characters. This intermediary structure adds minimal complexity to the process while ensuring complete and accurate character information is captured in the generated scripts.
3Device complexity
If only human body features are used for character identification, then the process is simpler, but recognition accuracy is insufficient due to voice variations
Solution Approach 1:
The patent merges human body feature extraction with voiceprint feature extraction to create a more robust character identification system. By combining these two feature types, the system overcomes the limitations of using only human body features (which may be similar for different characters) or only voice features (which may vary due to speech conditions). This combination significantly improves recognition reliability while adding manageable complexity.
Solution Approach 2:
The patent uses a composite approach by combining multiple feature types (human body features, voiceprint features, and text features) to identify characters. This composite feature set is more reliable than any single feature type alone, as it compensates for the weaknesses of individual features. The multi-feature composite identification maintains reasonable process complexity while dramatically improving character recognition accuracy and reliability.
Data Source
AI summary
A method for generating a video script, including: obtaining a target video; obtaining dialogue text information by performing speech recognition on speech segments in the target video; extracting a human body feature of a speaker from an frame associated with the speech segments in the target video, and extracting a voiceprint feature of the speaker from the speech segments; determining target feature information matching at least one of the human body feature of the speaker or the voiceprint feature of the speaker from a character library corresponding to the target video, and determining a target character corresponding to the target feature information in the character library; and generating the video script for the target video based on the target character and the dialogue text information.