Audio Transaction Tone Analysis for Receipt Tracking
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Solution Overview
Problem
Users face complexity in tracking and managing transactions due to the vast number of receipts generated, requiring manual review and high computing resources to identify items exceeding a certain threshold, while financial institutions often do not store itemized receipts due to privacy and complexity concerns.
Innovation Solution
A transaction analysis platform that analyzes audio signals from user devices to detect transaction tones, processes these signals to identify the quantity of items involved in a transaction, and generates transaction information, thereby reducing the need for manual review and conserving computing resources.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual review of receipts is performed to identify items exceeding a threshold, then transaction tracking accuracy is improved, but time consumption and computing resources increase significantly
Solution Approach 1:
The patent replaces the mechanical manual review process with an acoustic detection system. A microphone captures transaction tones emitted by POS devices, and audio processing algorithms automatically extract transaction information including item quantities and totals, eliminating the need for manual receipt review while maintaining high accuracy.
Solution Approach 2:
The patent introduces audio signals as an intermediary between the transaction system and the user. Instead of directly reviewing physical or digital receipts, users interact with processed audio information that contains encoded transaction details, enabling rapid and accurate transaction tracking without manual intervention.
2Loss of information
If itemized receipts are stored by financial institutions for transaction analysis, then transaction information completeness is improved, but user privacy concerns and system complexity increase
Solution Approach 1:
The patent extracts only the essential transaction information (item quantities, totals, timestamps) from the complete receipt data through audio processing. This selective extraction provides sufficient transaction tracking capability while minimizing data storage requirements and reducing system complexity compared to storing complete itemized receipts.
Solution Approach 2:
The transaction device itself generates and transmits the transaction tone containing encoded transaction information. The system processes this self-generated audio signal to extract necessary data, eliminating the need for external storage of detailed receipts by financial institutions while maintaining information completeness for tracking purposes.
3Productivity
If audio processing is performed to identify transaction tones and item quantities, then resource consumption is reduced, but processing complexity increases
Solution Approach 1:
The transaction device pre-encodes transaction information into specific audio tones during the transaction process itself. This preliminary encoding allows the receiving system to simply detect and count tones rather than performing complex analysis on raw receipt data, reducing processing complexity while improving resource efficiency.
Solution Approach 2:
The patent transforms transaction data into the audio domain, changing the parameter space from text-based receipt data to frequency-based sound waves. This parameter transformation enables the use of efficient audio processing algorithms that require fewer computational resources compared to traditional text analysis methods.
Data Source
AI summary
An example transaction analysis platform is described herein. The transaction analysis platform may analyze an audio signal to determine whether a user is associated with a transaction. The transaction analysis platform may determine that a tone of the audio signal is a transaction tone associated with the transaction. The transaction analysis platform may process, based on detecting the transaction tone, the audio signal to identify a set of tones associated with the transaction. The transaction analysis platform may generate, based on a quantity of the set of tones, transaction information associated with the transaction, wherein the transaction information identifies a quantity of items associated with the transaction, wherein the quantity of items corresponds to the quantity of the set of tones. The transaction analysis platform may perform an action associated with the transaction information and a transaction account of the user.


