Audio Quote Extraction via Text Verb and Quotation Mark Detection
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing methods for generating audio quotes from books are inefficient due to incomplete or inaccurate quotes, and the lack of awareness about available audio resources, making it difficult for users to identify quotes and their corresponding characters.
Innovation Solution
A system that analyzes text files to accurately extract and curate audio quotes by identifying quotation marks, communication verbs, and character names, using audiobook voices to provide accurate representations, and maintaining an index of available audio files for user selection.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If text-to-speech methods are used to generate audio quotes, then audio playback is enabled, but the quotes may be incomplete or include extra words making them unidentifiable
Solution Approach 1:
The system performs preliminary extraction and validation of quotes from text files before converting them to audio. By pre-identifying complete and accurate quotes using quotation mark detection and character name association, the system ensures quote accuracy before the text-to-speech conversion process, preventing incomplete or extra-word issues in the final audio output.
Solution Approach 2:
The system introduces an intermediary processing layer between the text file and audio output that includes quote extraction, validation, and character name association. This intermediary step filters and verifies quote completeness and accuracy before audio generation, resolving the contradiction between efficient audio production and precise quote representation.
2Device complexity
If default voice is used for audio playback, then audio generation is simplified, but the voice may not correspond to recognizable book character voices
Solution Approach 1:
The system applies local quality by associating specific character names with their corresponding audio quotes. Instead of using a uniform default voice for all quotes, the system enables users to select from multiple voice options that can be matched to specific characters mentioned in the quote metadata, allowing recognizable character voices while maintaining system simplicity through optional voice selection.
3Manufacturing precision
If manual curation is used to verify quotes, then quote accuracy is improved, but time consumption increases
Solution Approach 1:
The system performs self-service by automatically extracting, validating, and organizing quotes from text files using programmed algorithms for quotation mark detection, character name association, and quote completeness verification. This automated self-curation process eliminates the need for time-consuming manual review while maintaining high quote accuracy through systematic validation rules.
Solution Approach 2:
The system replaces the mechanical manual curation process with an automated computational system that uses text processing algorithms to identify quotes, validate their completeness, and associate them with character names. This substitution of mechanical human effort with automated computing processes maintains quote accuracy while dramatically reducing the time required for curation.
4Adaptability or versatility
If comprehensive audio resources are provided, then user selection capability is improved, but system complexity increases
Solution Approach 1:
The system segments audio resources into organized categories based on book titles, character names, and available voices. By dividing the comprehensive audio database into structured segments with metadata tags, the system enables users to easily search and select specific quotes and voices without being overwhelmed by the overall system complexity. The segmentation allows manageable organization of large audio resource collections.
Data Source
AI summary
Devices and methods are provided for extracting content from audio files. The device may determine starting and ending quotation marks in a text file, and a string between the starting and ending quotation marks. The device may determine that a verb is near the starting quotation mark or the ending quotation mark. The device may determine, based on the verb, that the string is attributed to a character name in the text file. The device may determine a first time in a first audio file including an audio representation of the text file, and may determine a second time in the first audio file, wherein the first time is before the first word and the second time is after the second word. The device may generate a second audio file by extracting audio from the first audio file based on the first and second times.