Ambient Noise Modification Using Mood-Aware Sound Masking
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Solution Overview
Problem
Ambient background noise from various devices in homes can be distracting and problematic, as it often interferes with users' activities and moods, and existing solutions fail to effectively modify noise based on individual mood and behavior.
Innovation Solution
A system that identifies ambient noise, user activity, and emotional state to determine a target noise, then uses associated devices to produce sound outputs that approximate the target noise, incorporating device capabilities and user feedback to modify the noise levels and types.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If ambient noise from devices is allowed to operate normally, then device functionality is maintained, but user distraction and discomfort increase
Solution Approach 1:
The patent converts harmful ambient noise into beneficial masking sound by analyzing the noise characteristics and generating complementary sounds that mask distracting frequencies. The system identifies noise sources and their acoustic profiles, then produces targeted sound outputs that neutralize the harmful effects while preserving device operation.
Solution Approach 2:
The system dynamically adjusts sound parameters including frequency, amplitude, and timbre based on real-time analysis of ambient noise and user state. By changing these acoustic parameters, the system optimizes the masking effect to reduce distraction while maintaining device functionality.
2Object-affected harmful factors
If noise modification is implemented to reduce distraction, then user comfort improves, but system complexity increases
Solution Approach 1:
The patent implements a multi-functional system where a single platform performs noise identification, acoustic analysis, sound generation, and user state monitoring. This universal approach consolidates multiple functions into one system, managing complexity through integration rather than proliferation of separate components.
Solution Approach 2:
The system automatically identifies noise sources, analyzes acoustic characteristics, determines appropriate masking strategies, and adjusts sound outputs without requiring manual user configuration. This self-service capability reduces the operational complexity burden on users while maintaining high user comfort.
3Adaptability or versatility
If noise modification is personalized based on user mood and activity, then noise effectiveness improves, but measurement and detection difficulty increases
Solution Approach 1:
The system incorporates feedback loops that continuously monitor user state through sensors and interactions, adjust noise modification parameters accordingly, and refine the personalization over time. This feedback mechanism enables accurate detection of user mood and activity states while maintaining system adaptability.
Solution Approach 2:
The system performs preliminary analysis of user preferences, typical activities, and environmental conditions to pre-configure noise modification strategies. This preliminary action reduces the real-time detection burden by establishing baseline parameters that are later fine-tuned based on actual user state.
Data Source
AI summary
Methods, systems, and media for ambient background noise modification are provided. In some implementations, the method comprises: identifying at least one noise present in an environment of a user having a user device, an activity the user is currently engaged in, and a physical or emotional state of the user; determining a target ambient noise to be produced in the environment based at least in part on the identified noise, the activity the user is currently engaged in, and the physical or emotional state of the user; identifying at least one device associated with the user device to be used to produce the target ambient noise; determining sound outputs corresponding to each of the one or more identified devices, wherein a combination of the sound outputs produces an approximation of one or more characteristics of the target ambient noise; and causing the one or more identified devices to produce the determined sound outputs.