Audio Object Delivery via Frequency Analysis
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Solution Overview
Problem
Existing communication systems face inefficiencies in processing audio data from multiple recording devices, leading to bottlenecks and delayed responses, as they struggle to distinguish human voices from environmental sounds and deliver relevant information to the correct user equipment.
Innovation Solution
A network server performs audible frequency analysis by segmenting audio clips into time bins, determining trigger sound frequencies, and calculating spectral flatness values to identify human voices, thereby efficiently assigning audio objects to the appropriate user equipment based on voice matrices and user profiles.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the network server processes all audio data from multiple recording devices, then comprehensive audio analysis is achieved, but processing time and system resources increase significantly
Solution Approach 1:
The patent segments audio data processing by dividing the audio spectrum into frequency bands and creating time bins for analysis. This segmentation allows the system to process specific frequency ranges and time periods independently, reducing overall processing time while maintaining comprehensive audio analysis capabilities.
Solution Approach 2:
The patent extracts only the relevant audio features needed for voice identification, specifically spectral flatness values and frequency band identifiers. By extracting only these critical features rather than processing entire audio files, the system achieves accurate voice detection with significantly reduced processing time and resource consumption.
2Reliability
If the system records environmental sounds continuously, then relevant voice commands are captured, but memory footprint expands and battery drains
Solution Approach 1:
The system extracts only essential audio features (spectral flatness and frequency band identifiers) from environmental sounds for transmission to the network server. This extraction approach ensures reliable voice command capture while minimizing local processing requirements and battery consumption on user equipment.
Solution Approach 2:
The patent performs preliminary audio feature extraction and filtering on user equipment before transmission. By preparing and filtering audio data in advance, the system ensures that only relevant information is transmitted and processed, reducing redundant processing cycles and energy consumption on both user equipment and network servers.
3Measurement precision
If the network server performs detailed spectral analysis on all audio clips, then accurate voice identification is achieved, but processing complexity and computational resources increase
Solution Approach 1:
The patent extracts only two critical features for voice identification: spectral flatness values and frequency band identifiers. By focusing on these specific extracted features rather than performing comprehensive spectral analysis, the system achieves accurate voice identification with significantly reduced processing complexity and computational resource requirements.
Data Source
AI summary
A system for audio object delivery based on audible frequency analysis comprises a network server comprising non-transitory memory storing an application that, in response to execution, the network server: ingests a plurality of audio clip messages that each comprise metadata and an audio clip file. For at least one audio clip message, the network server reduces the audio clip file to a predefined time length, creates a plurality of time bins, determines that a first time bin and a second time bin correspond with a trigger sound frequency, generates a spectral flatness value, determines a frequency band identifier, and appends the generated spectral flatness value and the frequency band identifier to the audio clip message. The network server assigns the appended audio clip message to a voice matrix, identifies user equipment based on the voice matrix, and initiates delivery of an audio object to the identified user equipment.