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Related Concept Videos

Masking and Demasking Agents01:19

Masking and Demasking Agents

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EDTA titrations may necessitate masking and demasking agents to temporarily protect a particular metal ion in a mixture from the EDTA reaction. These agents facilitate the sequential analysis of the metal ions by forming stable complexes with some—but not all—metal ions during certain steps.
There are many masking agents, such as cyanide, fluoride, triethanolamine, thiourea, and 2,3-bis(sulfanyl)propan-1-ol (formerly 2,3-dimercapto-1-propanol), with the masking agent chosen based on...
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Cochlear Implant Surgery and Electrically-evoked Auditory Brainstem Response Recordings in C57BL/6 Mice
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Real-time embedded implementation of the binary mask algorithm for hearing prosthetics.

Valerie Hanson, Kofi Odame

    IEEE Transactions on Biomedical Circuits and Systems
    |November 8, 2013
    PubMed
    Summary
    This summary is machine-generated.

    We developed a real-time embedded system using the binary masking algorithm to enhance speech-in-noise intelligibility. This system achieved an 85% improvement in intelligibility with low latency.

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    Area of Science:

    • Digital Signal Processing
    • Speech Enhancement
    • Embedded Systems

    Background:

    • Speech-in-noise intelligibility is a significant challenge in various acoustic environments.
    • The binary masking algorithm has demonstrated effectiveness in improving auditory perception.
    • Real-time embedded implementations are crucial for practical applications.

    Purpose of the Study:

    • To present a real-time embedded implementation of the binary masking algorithm.
    • To evaluate the performance of this implementation in terms of latency and intelligibility improvement.

    Main Methods:

    • The binary masking algorithm was implemented on a Spartan 3A FPGA.
    • The implementation utilized a combination of parallel processing and hardware pipelining.
    • Performance was evaluated using objective intelligibility measures.

    Main Results:

    • The real-time embedded system achieved a low measured latency of 8.5 ms.
    • The highest measured improvement in short-time objective intelligibility reached 85%.
    • The implementation demonstrated the feasibility of real-time speech enhancement.

    Conclusions:

    • The real-time embedded binary masking algorithm significantly enhances speech-in-noise intelligibility.
    • The developed system offers a practical solution for improving auditory communication in noisy environments.
    • Hardware acceleration on FPGAs enables efficient real-time processing for speech enhancement applications.