Context-Based Audio Filter Selection for Human and Speech Recipients
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Electronic devices face challenges in selecting the most suitable audio filters for audio signals, as different recipient processes perform better with different types of filters, leading to inefficient processing of audio signals.
Innovation Solution
An apparatus comprising a microphone array, processor, and memory that determines the recipient type of an audio signal and selects an appropriate audio filter, such as a beamforming filter for human destinations or a diction filter for speech recognition, using a type module and filter module to optimize audio signal processing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If a single audio filter is used for all recipient processes, then the device complexity is reduced, but the processing effectiveness for different recipient types deteriorates
Solution Approach 1:
The system dynamically selects audio filters based on the recipient type rather than using a static single filter. The filter selection module changes the filter configuration in real-time according to whether the recipient is a human destination or speech recognition system, optimizing processing effectiveness for each case.
Solution Approach 2:
Different audio filters are applied to different recipient types. Human destinations receive filters optimized for natural sound quality, while speech recognition recipients receive filters optimized for speech clarity and recognition accuracy, making each part of the system have the quality needed for its specific function.
2Reliability
If different audio filters are used for different recipient processes, then the processing effectiveness is improved, but the device complexity increases
Solution Approach 1:
The system performs preliminary classification of the recipient type before applying the appropriate filter. By determining whether the recipient is human or speech recognition in advance, the system can select the optimal filter without adding complex real-time adjustment mechanisms during audio processing.
Solution Approach 2:
A single filter selection module serves multiple functions by handling both human destination and speech recognition recipient types. The module universally manages filter selection for different recipient kinds, reducing the need for separate filter management systems for each recipient type.
3Ease of operation
If audio filters are not optimized for specific recipient types, then the ease of operation is improved, but the communication and recognition accuracy deteriorates
Solution Approach 1:
The filter selection system automatically determines the recipient type and selects the appropriate filter without requiring manual configuration or user intervention. The system serves itself by making intelligent decisions about filter selection based on recipient characteristics, maintaining ease of operation while optimizing accuracy.
Solution Approach 2:
The system uses information about the recipient type as feedback to select the appropriate filter. By receiving feedback about whether the recipient is human or speech recognition, the system can adjust filter selection to optimize recognition accuracy and communication effectiveness for each recipient kind.
Data Source
AI summary
For context-based audio filter selection, a type module determines a recipient type for a recipient process of an audio signal. The recipient type includes a human destination recipient type and a speech recognition recipient type. A filter module selects an audio filter in response to the recipient type.