Automatic Voice Frequency Conversion for Clearer TV Dialogue
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Solution Overview
Problem
Older individuals with hearing impairments face difficulties in clearly hearing conversations in media, and users must manually adjust sound settings when switching between music and talk shows, which is inconvenient.
Innovation Solution
A sound adjustment system with a sound receiving module, identification module, frequency conversion module, and equalizer that automatically identifies sound types and adjusts sound signals accordingly, using voice recognition technology to enhance voice clarity and apply music settings as needed.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If manual sound adjustment is used, then users can customize sound settings for different types of content, but users must manually switch settings when changing content types which is inconvenient
Solution Approach 1:
The system automatically identifies the type of audio content being played and autonomously adjusts the equalizer settings without requiring user intervention. The sound adjustment module detects content type (music, talk show, movie, etc.) and automatically applies appropriate sound profiles, making the system self-adjusting and eliminating manual operation needs.
Solution Approach 2:
The system continuously monitors the audio content being played, identifies its type in real-time, and dynamically adjusts sound settings based on the detected content. This closed-loop feedback mechanism ensures that sound settings automatically adapt to changing content types, preventing the need for manual switching and reducing time loss.
2Measurement precision
If frequency conversion is applied to voice signals, then clarity for hearing-impaired individuals is improved, but the system must accurately distinguish voice from non-voice signals to avoid inappropriate processing
Solution Approach 1:
The system introduces a sound identification module as an intermediary between the audio input and sound adjustment processes. This module analyzes audio characteristics (such as spectral features, temporal patterns, and energy distribution) to distinguish voice from non-voice content, enabling accurate automatic classification without requiring complex user-configurable parameters or manual intervention.
Data Source
AI summary
A sound adjustment method applied to a sound adjustment system is disclosed. The sound adjustment system includes a sound receiving module, a sound identification module, a sound frequency conversion module and a sound equalizer. The sound adjustment method includes the steps of: receiving a sound signal via the sound receiving module; identifying the sound signal via the sound identification module to determine a type of the sound signal; if the sound signal is a voice signal, executing a frequency conversion of the voice signal via the sound frequency conversion module such that the voice signal becomes a frequency-converted voice signal; if the sound signal is a non-voice signal, adjusting the non-voice signal via the sound equalizer such that the non-voice signal becomes an equalizer-adjusted sound signal.