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相关概念视频

Echo01:06

Echo

504
The human ear cannot distinguish between two sources of sound if they happen to reach within a specific time interval, typically 0.1 seconds apart. More than this, and they are perceived as separate sources.
Imagine the sound is reflected back to the ears. Assuming that the source is very close to the human, the difference between hearing the two sounds—the emitted sound and the reflected sound—may be more than the minimum time for perceiving distinct sounds. If this is the case,...
504
Perception of Sound Waves01:01

Perception of Sound Waves

4.4K
The human ear is not equally sensitive to all frequencies in the audible range. It may perceive sound waves with the same pressure but different frequencies as having different loudness. Moreover, the perception of sound waves depends on the health of an individual's ears, which decays with age. The health of one's ears may also be affected by regular exposure to loud noises.
The pitch of a sound depends on the frequency and the pressure amplitude of the source. Two sounds of the same...
4.4K
Sampling Continuous Time Signal01:11

Sampling Continuous Time Signal

226
In signal processing, a continuous-time signal can be sampled using an impulse-train sampling technique, followed by the zero-order hold method. Impulse-train sampling involves the use of a periodic impulse train, which consists of a series of delta functions spaced at regular intervals determined by the sampling period. When a continuous-time signal is multiplied by this impulse train, it generates impulses with amplitudes corresponding to the signal's values at the sampling points.
In the...
226
IR Spectrum Peak Splitting: Symmetric vs Asymmetric Vibrations01:08

IR Spectrum Peak Splitting: Symmetric vs Asymmetric Vibrations

970
Identical bonds within a polyatomic group can stretch symmetrically (in-phase) or asymmetrically (out-of-phase). Similar to hydrogen bonding, these vibrations also influence the shape of the IR peak. Generally, asymmetric stretching frequencies are higher than symmetric stretching frequencies. For example, primary amines exhibit two distinct IR peaks between 3300–3500 cm−1 corresponding to the symmetric and asymmetric N-H stretching, while secondary amines exhibit a single...
970
Reconstruction of Signal using Interpolation01:10

Reconstruction of Signal using Interpolation

191
Signal processing techniques are essential for accurately converting continuous signals to digital formats and vice versa. When a continuous signal is sampled with a period T, the resulting sampled signal exhibits replicas of the original spectrum in the frequency domain, spaced at intervals equal to the sampling frequency. To handle this sampled signal, a zero-order hold method can be applied, which creates a piecewise constant signal by retaining each sample's value until the next...
191
Sound Waves: Interference00:53

Sound Waves: Interference

3.7K
Sound waves can be modeled either as longitudinal waves, wherein the molecules of the medium oscillate around an equilibrium position, or as pressure waves. When two identical waves from the same source superimpose on each other, the combination of two crests or two troughs results in amplitude reinforcement known as constructive interference. If two identical waves, that are initially in phase, become out of phase because of different path lengths, the combination of crests with troughs...
3.7K

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相关实验视频

Updated: Jun 21, 2025

Microfluidic Platform with Multiplexed Electronic Detection for Spatial Tracking of Particles
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在嵌入式系统中实现声音方向检测和混合源分离.

Jian-Hong Wang1, Phuong Thi Le2, Weng-Sheng Bee3

  • 1School of Computer Science and Technology, Shandong University of Technology, Zibo 255000, China.

Sensors (Basel, Switzerland)
|July 13, 2024
PubMed
概括

这项研究使用嵌入式音频定位和增强算法增强可穿戴设备语音识别. 这些方法通过分离混合音频源来提高准确性,从而提高噪音环境中的性能.

关键词:
嵌入式系统 嵌入式系统混合声源隔离器 混合声源隔离器位置检测 位置检测信号与干扰比 (SIR) 是指信号与干扰的比.语音识别 语音识别 语言识别

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科学领域:

  • 计算机科学 计算机科学
  • 电气工程 电气工程
  • 信号处理 信号处理

背景情况:

  • 可穿戴设备和传感器网络是IT行业对健康和活动监控的关键.
  • 在嵌入式系统中增强语音识别对于改善用户与可穿戴技术的交互至关重要.
  • 音频信号处理技术对于克服环境噪音和可穿戴设备中的干扰至关重要.

研究的目的:

  • 实施和评估嵌入式系统的音频定位和增强算法.
  • 通过先进的信号处理来提高可穿戴设备的语音识别能力.
  • 在不同的嵌入式平台上展示方向检测和混合源分离算法的有效性.

主要方法:

  • 在TI TMS320C6713 DSK上实施的方向检测算法.
  • 混合源分离算法开发并测试在树派2.
  • 使用信号与干扰比率 (SIR) 和语音识别精度对混合源分离的实验性评估.

主要成果:

  • 混合源分离算法在1米处实现了平均SIR16.72,在2米处达到15.76.
  • 当使用开发的音频增强算法时,语音识别准确度显著提高到95%.
  • 在专门的嵌入式硬件上成功实现不同的音频处理算法.

结论:

  • 嵌入式音频定位和增强算法可以显著提高可穿戴设备的语音识别.
  • 开发的混合源分离技术有效地提高了嵌入式系统中的音频质量.
  • 这项研究为更强大,更准确的语音控制可穿戴技术提供了基础.