Machine Translation Channel With Accent Tuning for Clearer Calls
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Solution Overview
Problem
Offshoring of business services often leads to language barriers and miscommunication due to accent, grammar, cultural differences, and electronic connection quality issues between service providers and recipients, which can result in customer refusal to engage.
Innovation Solution
A communication system using machine learning to correct and translate language in real-time, adjusting accent, speed, and inserting filler phrases to enhance understanding, while providing feedback on translation quality.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of energy
If offshoring services to reduce costs, then business cost decreases, but language barrier and miscommunication increase
Solution Approach 1:
The patent introduces machine learning-based translation and accent modification systems as intermediaries between offshore service providers and customers. These systems translate speech between languages and modify accents to improve clarity, enabling cost-effective offshoring while maintaining communication accuracy through automated language mediation.
Solution Approach 2:
The patent replaces human language processing capabilities (speaking and understanding multiple languages and accents) with automated machine learning systems. This substitution allows offshore operations to maintain high communication quality without requiring expensive multilingual human agents, thus reducing costs while preserving information accuracy.
2Loss of information
If using machine learning translation in real-time, then communication understanding improves, but system complexity increases
Solution Approach 1:
The patent combines multiple machine learning functions (translation, accent modification, speech-to-text conversion) into an integrated communication system. By merging these functions into a unified platform, the system manages complexity through consolidation while delivering comprehensive language support for improved communication understanding.
Solution Approach 2:
The patent creates a universal communication system that handles multiple languages, accents, and communication modes (speech and text) through a single machine learning platform. This multi-functional approach improves communication understanding across diverse scenarios while avoiding the complexity of separate specialized systems.
3Loss of information
If modifying speech characteristics (accent, speed), then communication clarity improves, but naturalness of conversation decreases
Solution Approach 1:
The patent dynamically adjusts speech parameters (accent, speed, tone) using machine learning to optimize communication clarity. The system modifies these parameters in real-time based on the specific communication context and recipient preferences, improving clarity while attempting to maintain naturalness through adaptive parameter tuning rather than fixed transformations.
Data Source
AI summary
Technology is described for adding inserted message data into machine learning modified communications. The method can include receiving message data from a sender to be sent to a recipient. Another operation may be estimating a conversion time to convert the message data to a second language that is different than a language of the sender, using a machine learning translation service. A message insert may be provided or identified that approximates the conversion time. The message insert to be reproduced for the recipient may be sent. The message data may be sent to the recipient as converted to the second language.