Word Buffer Number Conversion Method
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing technologies face challenges in efficiently converting number words from text or speech data into numerical data, particularly in handling variations in word representation and filler words, which can lead to inefficiencies and resource-intensive processing.
Innovation Solution
A computer-implemented method utilizing a word buffer to identify and convert number words into numbers, including steps to handle filler words and determine when to convert the buffer into numbers, minimizing resource usage and ensuring coherent conversion.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If existing technologies are used to convert number words from text or speech data into numerical data, then the conversion can be performed, but the processing becomes resource-intensive and inefficient due to handling variations in word representation and filler words
Solution Approach 1:
The patent segments the text input into individual words and stores them in a word buffer, then processes them sequentially. This segmentation allows the system to handle number words and filler words separately, improving conversion efficiency by focusing processing resources only on relevant number words rather than processing entire text blocks uniformly.
Solution Approach 2:
The patent performs preliminary actions by first identifying and storing potential number words in a word buffer before actual conversion. The system checks each word against a number word dictionary in advance, preparing the data structure for efficient batch conversion later, which reduces overall processing resources required.
2Measurement precision
If all words in the text input are processed to identify number words, then accurate conversion can be achieved, but the processing time and resource usage increase
Solution Approach 1:
The patent extracts only the relevant number words from the text input by comparing each word against a number word dictionary, storing them separately in a word buffer. This extraction approach maintains identification accuracy by thorough checking while reducing processing time by avoiding unnecessary operations on non-number words.
Solution Approach 2:
The patent applies different processing quality to different types of words: number words receive full validation and conversion processing, while non-number words (including filler words) receive minimal or no processing. This local quality approach maintains accuracy for number words while significantly reducing overall processing time.
3Stability of the object's composition
If filler words are included in the conversion process, then the text coherence is maintained, but the conversion efficiency decreases due to unnecessary processing
Solution Approach 1:
The patent converts the potential harm of filler words (reducing conversion efficiency) into a benefit by using them as delimiters to identify number word boundaries. Filler words are detected and used to trigger conversion of accumulated number words, maintaining text coherence while actually improving conversion efficiency by structuring the processing flow.
Solution Approach 2:
The patent discards filler words from the number word buffer (not converting them to numbers) while recovering the number words that appear between filler words for conversion. This approach maintains text coherence by preserving the structure of filler words in the output while improving conversion efficiency by processing only the essential number words.
Data Source
AI summary
According to an embodiment, a computer-implemented method for obtaining at least one number based on a word buffer comprises: obtaining a word buffer; filling a number word buffer based on the word buffer by repeatedly obtaining a word from the word buffer, checking whether the word is a number word, and, in response to the word being a number word, adding the word to the number word buffer; in response to at least one preconfigured condition being met, converting the number word buffer into at least one number; and adding the at least one number to a result buffer.