DSP与Always-on功能

以下内容来自于CEVA。原文连接 - https://www.ceva-dsp.com/ourblog/how-dsp-supports-always-on-functions/

对于需要Always-on的功能,比如说语音控制或者,设备需要实时获取并实时处理传感器数据,而DSP是最佳的选择。

想象你正在询问智能音箱最近的寿司店在哪里,模拟到数字的转换电路将你的语音输入转换为零或者一的数字信号。随后DSP接收到并分析数字信号将其转换为可供处理的语句。随后,将反馈以数字的形式输入到数字模拟电路,转换为人可以理解的声音。

假设(hypothetically)我们用模拟信号处理器来处理,则会相当的复杂。此外(additionally),任何对处理算法的改变都需要硬件的相应的优化。相反(By comparison),DSP则要灵活的多。

DSP广泛的应用于各种电子设备中。在特定的应用中,增强的信号质量可以提供人甚至无法感知的信息和细节,比如对医学图像信号的处理。

DSP是人工智能应用的核心部件,包括自然语言处理。NLP可以使设备理解和分析人类语音和行为。

特别是在标准化的信号编解码应用中。模拟信号会产生畸变(distortion),干扰,甚至是安全漏洞(security breaches)。DSP对于现需要加密,压缩,快速传输(rapid transmission)等高速应用(high-speed applications)是很好的选择。

Sensor Hub可以将各种传感器信号处理从CPU转移开来(offload the work of sensor fusion),DSP同样如此,如需消耗CPU资源就可以进行多任务处理。

对于各种Always-on应用,嵌入式的DSP可以提供高性价比,低功耗解决方案,满足设备能耗要求。

Always-on在后台运作,可以处理复杂的传感器数据组合,比如IMU,语音。典型的Always-on应用包括 -

  • 智能手机和穿戴设备的计步器(pedometers)和GPS
  • 车道辅助(Lane assist)和成员检测
  • 语音控制

在传感器应用中,传感器手机包括光线 ,声音,3D移动和相关位置信息。一些多轴传感器,可以通过Sensor fusion处理数据。而DSP不但可以处理传感器数据,还可以将其他传感器数据进行更复杂的合并处理。

大部分的智能音频,视频和图像处理设备需要语音控制和物体监测功能。专门的DSP可以与CPU同步处理多种不同的复杂功能。

总结如下 -

  • Short overview of DSP:
    • DSP uses digital signal processing to convert and analyze signals such as audio, video, voice, light, temperature, pressure or position, and then output usable data
    • Analog converter takes this real-world information (such as light or sound waves) and turns it into a digital format (binary code); then, DSP technology processes this code and feeds the digitized information back out; this process is performed very quickly
  • DSP is used in many electronic applications
    • A computer may use DSP to monitor security, transmit telephone calls, compress video or play a movie on a home theater system
    • In certain applications, the quality of the signal is enhanced to provide even more information and detail than what humans are able to sense – for example, a computer enhancing medical images
  • Analog signal processing is also possible, but the process is made much faster and more efficient with digital signal processing – improves speed and accuracy
    • I’ve talked before about how a sensor hub can be used to offload the work of sensor fusion from the main CPU of your device, and a DSP offers the same benefit, allowing you to run multiple functions without overtaxing your primary CPU
    • In sensing applications, sensors are gathering information on light, sound, or, if it’s a motion sensor, 3D movement and relative location; in AR/VR this might mean tracking hand motions; in robotics, this means mapping out surrounding objects and relaying that data to avoid crashes
    • Some multi-axis sensors, like IMUs, do their own data processing via sensor fusion to blend several inputs, such as from a gyroscope and an accelerometer. A DSP can then process inputs (signals) from multiple sensors of different types, and this could include contextual motion data that’s already been processed via sensor fusion and is now being added to additional sensor data (such as light, sound, etc.) to tell a comprehensive story
    • Always-on functions operate in the background, and can be a combination of multiple sensor types, such as IMU/Voice/other (e.g. presence detection) for more comprehensive context
    • Embedded DSPs can handle all of these always-on functions in real-time, which is critical to performance without slowing down the CPU or draining its battery – offers a more cost-effective, low-power solution.
    • Example always-on functions: pedometers, GPS, lane assist or passenger detection in cars, voice control on TV remotes
    • Most smart audio and video/imaging applications require at least some of these types of always-on voice control and object detection functions
    • On a DSP, these computations can be run in parallel with the CPU, so that many different functions can be carried out at the same time
    • More flexible hardware interpretation
    • Easier to be used across a variety of devices because the encoding and decoding techniques are standard
    • Encryption and compression help with security as well as efficient transmission and downloading
    • Analog signals were used traditionally for long distances, but are prone to distortion, interference and even security breaches
    • Along with higher speed and accuracy, digital signal processing offers a number of benefits, including:
    • By running a small always-on DSP, you can enable functions in the background:

本文分享自微信公众号 - VoiceVista语音智能(AIndustrialRock),作者:深思睿

原文出处及转载信息见文内详细说明,如有侵权,请联系 yunjia_community@tencent.com 删除。

原始发表时间:2019-11-28

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