MUMBAI, India, Nov. 2 -- Intellectual Property India has published a patent application (202631125234 A) filed by Dr. Bhawesh Kumar Bhargav on October 21, 2026, for An Intelligent English Pronunciation Assessment System Using Phoneme-Level Speech Pattern Analysis.
Inventor includes Dr. Bhawesh Kumar Bhargav.
The application for the patent was published on October 30, 2026, under issue no. 44/2026.
Abstract: ABSTRACT [505] The present invention introduces an advanced intelligent English pronunciation assessment system that integrates phoneme-level speech pattern analysis with real-time acoustic evaluation frameworks and adaptive feedback-generation mechanisms, facilitating dynamic pronunciation scoring, phoneme-level error identification, and robust assessment confirmation while maintaining seamless educational integration and operational accuracy for consistent language-learning applications. [510] The comprehensive assessment framework employs adaptive machine-learning algorithms and acoustic-modelling protocols, utilising embedded computational processing arrays and resource-efficient inference systems to ensure timely phoneme identification, enhanced pronunciation understanding, and optimal feedback reliability while maintaining continuous speech-monitoring capabilities across learners and accents. [515] The integrated methodology combines multi-feature acoustic acquisition techniques with artificial-intelligence-driven pattern recognition systems, leveraging variable-confidence phoneme signals and multi-factor mispronunciation indicators to optimise assessment procedures and feedback workflows for maximum evaluation accuracy and minimal scoring uncertainty during critical educational applications. [520] The novel responsive assessment architecture features engineered high-fidelity speech-processing components with specialised phoneme-fingerprinting protocols, enabling complex multi-stage pronunciation verification while ensuring scoring consistency and performance optimisation across various learner configurations and native-language backgrounds without compromising system reliability. [525] The innovative design incorporates strategic validation mechanisms for enhanced phoneme identification and assessment integrity, utilising optimised multi-feature systems and adaptive scoring technology to ensure legitimate pronunciation evaluation while maintaining functionality across diverse educational environments and assessment scenarios. [530] Implementation methodology emphasises scalable assessment integration and efficient evaluation sequences, implementing interactive feedback measures and pattern-recognition algorithms to achieve superior phoneme determination, enhanced error identification, and mispronunciation correction while ensuring technological simplicity during educational monitoring. [535] The system demonstrates exceptional adaptability through comprehensive integration of phoneme-identification protocols and intelligent assessment technologies, validating its effectiveness across various language-learning configurations and learner scenarios while maintaining consistent assessment performance and operational efficiency under diverse conditions. [540] The developed framework enables sustainable and reliable assessment of English pronunciation through streamlined, AI-powered evaluation systems, providing significant advantages over traditional manual approaches through adaptive feedback mechanisms, phoneme-level identification protocols, and improved scoring assignment while maintaining superior assessment accuracy during critical educational pronunciation procedures.
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