Audio Stream Classification via Bitrate Analysis
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Solution Overview
Problem
Current speech-to-text technologies face challenges in distinguishing between real-time and non-real-time audio streaming, leading to increased costs and reduced accuracy due to the need for different processing techniques and resource allocation.
Innovation Solution
A method that determines the bitrate of incoming audio data and calculates an R value to differentiate between real-time and non-real-time streams, allowing for the application of suitable speech-to-text techniques and resource prioritization based on the classification.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If speech-to-text processing is performed on all audio streams using the same method, then processing simplicity is maintained, but accuracy decreases and costs increase due to inappropriate processing techniques being applied to both real-time and batch audio
Solution Approach 1:
The patent segments audio streams into two distinct categories: real-time streams and batch streams. This segmentation is achieved by analyzing the bitrate characteristics of incoming audio data and comparing it against expected bitrate ranges. Once segmented, different speech-to-text processing techniques are applied to each category, with real-time streams receiving low-latency optimized processing and batch streams receiving high-accuracy optimized processing, thereby resolving the contradiction between maintaining processing simplicity and achieving high accuracy.
2Speed
If real-time processing techniques are applied to all audio streams, then latency requirements are met, but computational resources are wasted on batch processing tasks that could use more efficient batch methods
Solution Approach 1:
The patent implements dynamic resource allocation by continuously monitoring audio stream characteristics and adjusting processing techniques accordingly. The system dynamically determines whether each audio stream is real-time or batch based on bitrate analysis, then dynamically assigns appropriate processing resources. This dynamic approach ensures that real-time streams receive the computational resources necessary for low-latency processing while batch streams are processed using more resource-efficient methods, thereby eliminating computational resource waste while maintaining processing speed requirements.
3Productivity
If batch processing methods are used for all audio streams, then computational efficiency is improved, but real-time streams suffer from unacceptable latency
Solution Approach 1:
The patent applies the principle of local quality by tailoring the processing methodology to the specific characteristics of each audio stream. Rather than applying a uniform batch processing method to all streams, the system analyzes local characteristics (bitrate, timing patterns) of each stream and applies the appropriate processing quality level. Real-time streams receive high-priority, low-latency processing optimized for speed, while batch streams receive standard processing optimized for computational efficiency, thereby resolving the contradiction between productivity and latency.
4Reliability
If audio streams are not classified, then resource allocation is simplified, but costs increase due to inability to prioritize latency-critical audio jobs
Solution Approach 1:
The patent employs parameter changes by monitoring specific parameters of incoming audio streams (bitrate, timing intervals, data patterns) to classify streams as real-time or batch. The system changes the processing parameter (priority level, processing method) based on the classification result. This parameter-based classification approach enables the system to prioritize latency-critical real-time audio jobs while maintaining simplified resource allocation rules, thereby improving quality of service without introducing excessive classification complexity.
Data Source
AI summary
One or more audio data is received. An expected bitrate of the one or more audio data is determined. An input bitrate of the one or more audio data is determined. An R value using the expected bitrate and the input bitrate is determined. The R value is compared to an R threshold.