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采用深度学习模型来评估听觉植入物的声学模拟中的语音信息

Rahul Sinha¹, Mahan Azadpour¹

¹New York University Grossman School of Medicine.

Research square

|July 18, 2023

概括

一个新的深度学习模型模拟了听觉植入物对语音感知的影响,为人类测试提供了更快,更便宜,更一致的替代方案. 这种人工智能方法模仿了人类的反应,推进了神经假体的开发.

科学领域:

生物医学工程生物医学工程
人工智能的人工智能
神经科学是一个神经科学.

背景情况:

声学模拟对于在听觉神经植入物中开发语音处理和声音编码至关重要.
传统的人体对这些模拟的测试是耗时的,昂贵的,容易发生个体变化.
评估信号处理和单个因素对语音感知的影响需要高效的模拟方法.

结论:

这种深度学习方法为听力植入物模拟提供了更快,更具成本效益和更少变量的方法.
消除了注意力和学习等人类特有的变量,提供了更客观的数据.
为有效评估听力植入体模拟和开发神经假体技术铺平了道路.

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相关概念视频

Hearing

Hearing

When we hear a sound, our nervous system is detecting sound waves—pressure waves of mechanical energy traveling through a medium. The frequency of the wave is perceived as pitch, while the amplitude is perceived as loudness.