Accent-Personalized Speech Processing for Clearer Virtual Meetings
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Solution Overview
Problem
Virtual meetings face challenges in communication among non-native and native English speakers due to accent differences, leading to comprehension issues.
Innovation Solution
A system and method that converts non-native English accents to a preconfigured native English accent and personalizes the audio data to the listener's accent using machine learning models, enabling effective communication.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If all participants communicate in a common language (e.g., English), then virtual meetings can be conducted across different locations and countries, but non-native speakers experience comprehension loss due to accent differences
Solution Approach 1:
The patent introduces an intermediary system (accent neutralization and personalization system) that mediates between speakers with different accents and listeners. The system captures audio input, neutralizes accents to a standard form, and transmits the processed audio to listeners, thereby eliminating comprehension barriers while preserving the ability to communicate across different locations and countries.
Solution Approach 2:
The patent changes the acoustic parameters of the audio signal by applying accent neutralization processing. This involves modifying phonetic characteristics, pronunciation patterns, and spectral features of the speech signal to transform non-native accents into a neutral standard accent, thereby improving comprehensibility without changing the linguistic content.
2Loss of information
If accent neutralization is applied to improve comprehension, then understanding between speakers and listeners improves, but the system complexity increases
Solution Approach 1:
The patent extracts the accent characteristics from the speech signal separately from the linguistic content. By isolating and processing only the accent-related acoustic features while preserving the core message, the system achieves effective accent neutralization with reduced computational complexity compared to processing the entire speech signal.
Solution Approach 2:
The patent segments the audio processing into distinct stages: accent detection, accent neutralization, and personalized output generation. This segmentation allows each module to be optimized independently and enables the system to handle complex processing tasks through a series of simpler, manageable steps.
3Loss of information
If accent personalization is implemented for each listener, then communication clarity improves for non-native speakers, but the processing time and computational resources increase
Solution Approach 1:
The patent performs preliminary accent neutralization processing on the audio signal before distribution to listeners. By pre-processing the audio to remove accent barriers and then efficiently applying personalized adjustments only when needed, the system reduces real-time processing requirements and minimizes delays in audio transmission.
Solution Approach 2:
The patent applies full accent neutralization processing universally to all audio inputs, ensuring that every listener receives comprehensible audio regardless of their native language. This excessive application of the processing ensures comprehensive coverage while allowing individual listeners to receive personalized adjustments only when their specific needs require them.
Data Source
AI summary
In one aspect, an example methodology implementing the disclosed techniques includes, by a computing device, receiving audio data corresponding to a spoken utterance by a first user and determining an accent of the audio data. The method also includes, by the computing device, neutralizing the accent of the audio data to a preconfigured accent and transmitting a modified audio data in the preconfigured accent to another computing device. The modified audio data includes the spoken utterance by the first user.