A neural cantonese speech converter using QCA for nanocomputing

IF 4 3区计算机科学 Q1 COMPUTER SCIENCE, HARDWARE & ARCHITECTURE

Computers & Electrical Engineering Pub Date : 2025-06-17 DOI:10.1016/j.compeleceng.2025.110536

Angshuman Khan , Rohit Kumar Shaw , Ali Newaz Bahar

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引用次数: 0

Abstract

This research explores the pioneering integration of Quantum-dot Cellular Automata (QCA) for designing a combinational neuro-fuzzy logic circuit within a feedforward neural network-based Cantonese speech converter. Cantonese, a tonal language with intricate phonetic structures, presents substantial speech recognition and synthesis challenges. The proposed QCA-based speech conversion circuit leverages the quantum mechanical tunnelling properties of quantum dots to achieve ultra-fast processing, minimal power dissipation, and enhanced energy efficiency, making it a highly suitable alternative to conventional speech recognition systems. The architectural design ensures precise phonetic recognition, tone preservation, and high intelligibility, optimizing real-time speech processing. Simulation results confirm that the circuit consumes only 2.338 nanowatts of power, demonstrating a 45 % enhancement in energy-delay cost compared to conventional speech recognition systems. Additionally, the proposed system achieves excellent recognition accuracy for frequently used Cantonese keywords in eBook reading applications. The study underscores QCA’s transformative potential in low-power nanocomputing, positioning it as a breakthrough technology for efficient, high-speed, and sustainable speech processing in next-generation natural language interfaces.

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基于QCA的纳米计算神经广东话语音转换器

本研究探索了量子点元胞自动机（QCA）在前馈神经网络广东话语音转换器中的开创性集成，以设计组合神经模糊逻辑电路。广东话是一种声调语言，语音结构复杂，对语音识别和合成提出了很大的挑战。所提出的基于qca的语音转换电路利用量子点的量子力学隧穿特性，实现超快速处理、最小功耗和提高能源效率，使其成为传统语音识别系统的非常合适的替代方案。架构设计确保了精确的语音识别、音调保存和高清晰度，优化了实时语音处理。仿真结果证实，该电路仅消耗2.338纳瓦的功率，与传统语音识别系统相比，能量延迟成本提高了45%。此外，该系统对电子书阅读应用中常用的广东话关键词的识别准确率较高。该研究强调了QCA在低功耗纳米计算方面的变革潜力，将其定位为下一代自然语言接口中高效、高速和可持续语音处理的突破性技术。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Computers & Electrical Engineering 工程技术-工程：电子与电气

CiteScore

9.20

自引率

7.00%

发文量

661

审稿时长

47 days

期刊介绍： The impact of computers has nowhere been more revolutionary than in electrical engineering. The design, analysis, and operation of electrical and electronic systems are now dominated by computers, a transformation that has been motivated by the natural ease of interface between computers and electrical systems, and the promise of spectacular improvements in speed and efficiency. Published since 1973, Computers & Electrical Engineering provides rapid publication of topical research into the integration of computer technology and computational techniques with electrical and electronic systems. The journal publishes papers featuring novel implementations of computers and computational techniques in areas like signal and image processing, high-performance computing, parallel processing, and communications. Special attention will be paid to papers describing innovative architectures, algorithms, and software tools.