Audio Recall Buffer for Voice Conversation Information Retrieval
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Solution Overview
Problem
Existing technologies face challenges in real-time synchronization, aggregation, and analysis of communication data among multiple parties due to remoteness and lack of uniform communication devices, leading to difficulties in gathering and analyzing simultaneous communication data.
Innovation Solution
A method and system that involves client devices capturing and processing audio data, sending it to a speech recognition service for transcription, and then synchronizing and analyzing timestamped text transcripts with a communication backend to provide relevant data to participants, using a network to facilitate seamless communication and background analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If audio data is continuously captured and buffered for analysis, then the ability to recall and analyze past conversation information is improved, but the system complexity and processing requirements increase
Solution Approach 1:
The system pre-records and buffers audio data during conversations before recall is needed. The audio buffer continuously stores incoming audio data in real-time, so when a recall request occurs, the information is already prepared and available for immediate analysis without requiring complex on-demand recording mechanisms.
Solution Approach 2:
An audio buffer serves as an intermediary component between the audio input source and the analysis system. This buffer acts as a temporary storage medium that decouples the continuous audio stream from the intermittent recall requests, simplifying the overall system architecture by providing a standardized interface for both recording and analysis operations.
2Productivity
If real-time analysis of buffered audio data is performed, then relevant information can be provided during conversations, but processing time and computational resources increase
Solution Approach 1:
The system performs analysis selectively rather than continuously analyzing all buffered audio data. When a recall request is received, the system analyzes only the relevant portion of the buffered audio data corresponding to the recall timeframe, rather than processing the entire audio buffer, thus reducing computational overhead while still providing timely information.
3Adaptability or versatility
If multiple participants use different communication devices remotely, then communication flexibility and accessibility are improved, but synchronization and data gathering become more difficult
Solution Approach 1:
The system is designed to accept audio data from multiple different types of communication devices through a universal interface. The audio buffer and analysis system handle various audio formats and sources uniformly, allowing participants to use different devices (phones, computers, tablets) without requiring device-specific processing logic, thus maintaining synchronization reliability across diverse platforms.
Data Source
AI summary
Conversation information is provided to a conversation participant. Audio data is received a client device associated with a conversation participant. The client device maintains a buffer of received audio data, for instance audio data received in a previous interval of time. A recall request is received by the client device for information associated with the buffered audio data. The buffered audio data is analyzed responsive to the recall request to identify the requested information. The identified information is then presented at the client device.