Adaptive Media Playback for Accent and Noise Comprehension

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Solution Overview

Problem

Users face challenges in understanding media content due to language barriers, accents, and environmental noise, which affect the comprehension of audio and video content.

Innovation Solution

A media content optimizer utilizing neural networks to adjust playback speed and volume based on factors such as accent, language, and environmental noise, employing components like text generation, semantic analysis, confidence analysis, and adjustment determination to enhance user understanding.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Reliability

If media content is played at normal speed and volume, then the original content is preserved, but user understanding deteriorates when language barriers or background noise are present

Engineering Contradiction:

Improveuser understandingVSAvoidlanguage barrier and noise

Core Design Contradiction:

ReliabilityVSObject-affected harmful factors

Solution Approach 1:

The system dynamically adjusts playback speed and volume based on real-time analysis of media content characteristics (language, accent, noise levels) and user profile, transforming the static playback into an adaptive process that optimizes understanding for each segment of content

Inventive Principle:

Principle #15Dynamics

Solution Approach 2:

The system changes physical parameters of media playback (speed, volume) based on analyzed characteristics of the content and environmental factors, modifying these parameters to enhance comprehension while maintaining content integrity

Inventive Principle:

Principle #35Parameter changes

2Reliability

If playback speed is slowed down to improve understanding, then comprehension improves, but time consumption increases

Engineering Contradiction:

ImprovecomprehensionVSAvoidtime consumption

Core Design Contradiction:

ReliabilityVSLoss of time

Solution Approach 1:

The system applies different playback adjustments to different segments of media content based on local characteristics such as language complexity, accent difficulty, and noise levels, rather than uniformly slowing down the entire content

Inventive Principle:

Principle #3Local quality

Solution Approach 2:

The system applies playback adjustments selectively only when and where needed based on content analysis, avoiding unnecessary slowing down of clear segments while intensively adjusting difficult segments for comprehension

Inventive Principle:

Principle #16Partial or excessive action

3Reliability

If playback volume is increased to overcome background noise, then audio clarity improves, but device power consumption increases

Engineering Contradiction:

Improveaudio clarityVSAvoidpower consumption

Core Design Contradiction:

ReliabilityVSUse of energy by moving object

Solution Approach 1:

The system dynamically adjusts volume as a variable parameter based on environmental noise analysis and content characteristics, optimizing audio clarity while minimizing unnecessary power consumption from sustained high-volume playback

Inventive Principle:

Principle #35Parameter changes

Data Source

PatentUS12431126B2Media engagement through deep learning

Publication Date: 2025.09.30 NVIDIA CORP

AI summary

Apparatuses, systems, and techniques to facilitate understanding of media content using neural networks to adjust playback speed and volume based on environmental and other factors. In at least one embodiment, playback of media content is slowed down or sped up if audio associated with said media content is difficult to understand based on background noise, accent, difficulty of material, as well as other factors that decrease understandability of media content.