基于STM32的语音采集与分析系统设计
摘 要
自从人类社会进入到由人工智能主导的第四次工业革命，世界进入了万物互联的物联网时代。人工智能的飞速发展对人类与智能产品的交互产生了深刻影响，人机交互不再局限于命令行代码或键盘鼠标输入，取而代之的是更为便捷和自然的语音交互，让我们的交互体验变得更加舒适与高效。而语音信号的采集与处理则是实现语音人机交互不可或缺的重要部分。
随着计算机技术和音频处理技术的发展，音频处理算法变得越来越复杂，采用传统的模拟信号处理方法实现这些算法不仅难度大、成本高，有的甚至无法实现。因此，使用微型计算机控制的数据采集与处理系统逐渐代替人力完成大量的重复性工作，由于处理速度快、精度高，已经成为现场采集语音数据的有效手段。
本设计主要是开发一种基于STM32微控制器的语音采集和分析系统。该系统的核心功能是能够实时采集并分析语音信号，通过快速傅里叶变换（FFT）技术对语音信号进行频谱分析，以提取语音中的特征信息，该系统能够根据这些特征信息有效地区分出男女声音。此外该系统还附加LU-ASR01语音识别模块，该模块使用了基于深度学习的语音识别算法，包含了语音指令转换为文本、语音指令识别等拓展功能，并提供给应用程序进一步处理，为后期多种功能的开发带来了更多选择。
经过全面的测试和评估，该系统表现出了良好的性能和稳定性，能够准确地区分出男女声音。这一设计为智能家居、智能安防、语音识别等领域提供了新的解决方案，具有广泛的应用前景和实际价值。
关键词：STM32； 频谱分析； 声音识别
ABSTRACT
Since human society has entered the fourth industrial revolution led by artificial intelligence, the world has entered the Internet of Things era of everything interconnected.The rapid development of artificial intelligence has had a profound impact on the interaction between humans and intelligent products. Human-computer interaction is no longer limited to command line codes or keyboard and mouse input, but rather more convenient and natural voice interaction, which makes our interaction experience more comfortable and efficient.And the acquisition and processing of speech signals are an indispensable part of the realization of voice human-computer interaction.
With the development of computer technology and audio processing technology, audio processing algorithms are becoming more and more complex. It is not only difficult and costly to implement these algorithms by using traditional analog signal processing methods, but also impossible to implement some of them.Therefore, the data acquisition and processing system controlled by microcomputers has gradually replaced human labor to complete a large number of repetitive tasks. Due to its high processing speed and high precision, it has become an effective means of collecting voice data on the spot.
This design is mainly to develop a voice acquisition and analysis system based on STM32 microcontroller. The core function of the system is to collect and analyze speech signals in real time. Through the Fast Fourier Transform (FFT) technology, the speech signal is analyzed by spectrum analysis to extract the feature information in the speech. According to these feature information, the system can effectively distinguish between male and female voices.In addition, the system also has LU-ASR01 speech recognition module. The module uses speech recognition algorithm based on deep learning, including speech command conversion to text, speech command recognition and other expansion functions, and is provided for further processing by the application program, which brings more choices for the development of various functions in the later stage.
After comprehensive testing and evaluation, the system has shown good performance and stability, and can accurately distinguish between male and female voices.This design provides a new solution for smart home, intelligent security, speech recognition and other fields, and has a wide range of application prospects and practical value.
Key words: STM32; Spectrum analysis; Voice recognition
目 录
插图清单 V
表格清单 VI
引言 - 1 -
1 绪论 - 2 -
1.1 研究背景及意义 - 2 -
1.2 发展概况 - 3 -
1.3 研究方法 - 3 -
1.4 研究的主要内容 - 4 -
1.5 论文应解决的关键问题 - 4 -
1.6 论文结构安排 - 4 -
2 系统方案论证 - 6 -
2.1 核心处理器选取 - 6 -
2.2 语音信号采样模块选取 - 7 -
2.3 语音特征提取方法选取 - 7 -
2.4 显示模块选取 - 8 -
3 硬件设计 - 10 -
3.1 硬件组成框图 - 10 -
3.2 STM32F407主控模块 - 10 -
3.2.1 STM32F407微控制器 - 10 -
3.2.2 STM32F407的最小系统 - 12 -
3.3 LU-ASR01模块 - 13 -
3.3.1 LU-ASR01简介 - 13 -
3.3.2 LU-ASR01工作原理 - 14 -
3.4 ILI9341液晶显示模块 - 16 -
3.5 电源模块 - 18 -
3.6 00 - 18 -
4 软件设计 - 19 -
4.1 软件的总体设计 - 19 -
4.2 循迹流程设计 - 20 -
5 调试与分析 - 22 -
5.1 硬件调试 - 22 -
5.2 软件调试 - 23 -
5.3 分析 - 24 -
5.3.1 遮光装置材料分析 - 24 -
5.3.2 传感器分析 - 25 -
5.3.3 小车速度分析 - 26 -
结论与展望 - 27 -
参考文献 - 29 -
附录A 原理图 - 30 -
附录B 主要参考文献的题录及摘要 - 32 -
附录C 主要源程序 - 35 -
参考文献
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