Automatic Caption Synchronization and Dynamic Positioning
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Solution Overview
Problem
Current methods for synchronizing captions with video streams in live TV broadcasts face challenges due to manual transcription delays, misalignments, and variability in spoken environments, leading to unsynchronized and distracting captions, which are costly and time-consuming to correct.
Innovation Solution
An automated method using automatic speech recognition to generate and synchronize captions by identifying anchor words, adjusting timestamps, and dynamically positioning captions based on visual content analysis to avoid overlap with other textual information.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual transcription is used to produce captions, then captions can be accurately transcribed, but there is a significant delay (up to 30 seconds) between audio stream and caption readiness
Solution Approach 1:
The patent replaces the manual mechanical transcription process with an automated system combining ASR (automatic speech recognition) and deep learning models. The system processes audio streams in real-time, generating captions without human intervention and eliminating the 30-second delay inherent in manual transcription while maintaining accuracy through sophisticated algorithms.
Solution Approach 2:
The system enables self-service caption generation where the automated ASR and deep learning model independently transcribe and synchronize captions without requiring human transcribers. The system self-corrects and self-adjusts timestamps, making the captioning process autonomous and eliminating dependency on manual human labor.
2Measurement precision
If ASR systems are used to synchronize captions, then synchronization accuracy can be improved, but the system becomes complex and requires extensive training data
Solution Approach 1:
The patent segments the complex synchronization task into multiple independent modules: ASR module for speech recognition, deep learning module for timestamp prediction, and alignment module for synchronization. Each module handles a specific sub-task, making the overall system more manageable and easier to train independently, reducing the complexity burden.
Solution Approach 2:
The system performs preliminary actions by pre-processing audio streams and extracting features before feeding them to the ASR and deep learning models. Timestamp predictions are generated in advance based on audio analysis, and alignments are pre-computed, reducing the complexity of real-time processing and enabling more accurate synchronization.
3Ease of manufacture
If captions are displayed at fixed positions, then implementation is simple, but captions may overlap with important visual information in the video
Solution Approach 1:
The patent transforms fixed caption positioning into dynamic positioning that automatically adapts to video content. The system analyzes each video frame to detect text regions and adjusts caption placement in real-time, ensuring captions are displayed on blank areas rather than overlapping with important visual information, while maintaining implementation feasibility through automated algorithms.
Data Source
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AI summary
« Method of automatically synchronizing a caption transcript, made of phrases having initial timestamps, with a video stream, comprising: a. generating an audio transcript of the video stream using automatic speech recognition, timestamps being associated to tokens of the audio transcript, b. tokenizing the caption transcript and assigning estimated timestamps to tokens, c. comparing tokens of the caption transcript with tokens of the audio transcript to identify anchor words in the caption transcript corresponding to tokens of the caption transcript matching with tokens of the audio transcript, d. assigning to the anchor words the timestamps of the corresponding tokens in the audio transcript, and e. shifting initial timestamps of the phrases of the caption transcript based on time differences between anchor words and corresponding tokens of the caption transcript so as to assign final timestamps to the phrases of the caption transcript and synchronize the caption transcript with the video stream. »