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The human brain perceives pitch through two primary mechanisms reflected in place theory and frequency theory. Each mechanism describes how sound waves are interpreted as specific pitches by the brain, offering insights into the intricate processes of auditory perception.
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Improving short-term memory can be achieved through techniques like chunking and rehearsal. Chunking involves organizing information into larger, more manageable units. This technique is particularly useful for information that exceeds the typical memory span of between five and nine items. For instance, logging into an online account with a password like "ta89vq0179gz" involves grouping letters and numbers into three chunks—ta89, vq01, and 79gz. It makes large amounts of...
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阵列配置-不可知性个性化语音增强使用长期-短期空间连贯性.

Yicheng Hsu1, Yonghan Lee1, Mingsian R Bai1

  • 1Department of Power Mechanical Engineering, National Tsing Hua University, No. 101, Section 2, Kuang-Fu Road, Hsinchu 30044, Taiwan.

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概括
此摘要是机器生成的。

本研究介绍了一种全新的多道个性化语音增强 (PSE) 系统. 它使用新的空间特征有效地抑制背景噪声,在不需要麦克风阵列细节的情况下实现卓越的性能.

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科学领域:

  • 信号处理 信号处理
  • 声学 声学 在声学方面
  • 机器学习 机器学习

背景情况:

  • 个性化语音增强 (PSE) 旨在抑制干扰语音.
  • 多通道PSE系统在杂的环境中比单通道方法具有优势.
  • 为各种家庭麦克风阵列实施多通道PSE是一项挑战.

研究的目的:

  • 开发一个数组配置不可知的多通道个性化语音增强 (PSE) 系统.
  • 引入一种新的空间特征,用于监测目标音箱活动.
  • 为了评估系统在不利的声学条件下的性能.

主要方法:

  • 定义了一种新的空间特征,即具有动态遗忘因子的长短空间连贯性 (LSTSC).
  • 使用卷积循环网络,并将LSTSC功能作为输入.
  • 建议简化LSTSC功能,以降低计算成本.
  • 实验将拟议的PSE系统与基线进行比较,使用未见的房间响应和阵列配置.

主要成果:

  • 建议使用LSTSC训练的多通道PSE网络实现了卓越的语音增强.
  • 该系统在不需要精确了解阵列配置或房间响应的情况下证明了有效性.
  • 完整的和简化的LSTSC版本都显示出显著的性能改进.

结论:

  • 开发的LSTSC功能可以实现数组配置无关的多通道PSE.
  • 拟议的系统为复杂的声学环境中语音增强提供了强大的解决方案.
  • 这种方法在现实场景中推进了多道PSE的实际应用.