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所在平台: Udemy |
课程主页: https://www.udemy.com/course/speaker-recognition/
课程评论：没有评论
课程名称：获奖教科书作者讲授的说话人识别 课程简介：本课程是对说话人识别技术的介绍。说话人识别位于音频处理、生物识别和机器学习的交叉点，具有多种应用。你可以在智能手机、智能家居设备以及各种商业服务中找到说话人识别的应用。本课程将从说话人识别技术的历史入手，了解其从简单的人力努力演变为现代基于深度学习的智能系统的过程。我们将涵盖声学、感知、音频处理、信号处理和特征提取的基础知识，因此即使没有这些领域的背景也不会感到困难。 课程还将介绍一些流行的机器学习方法，例如高斯混合模型、支持向量机、因子分析和神经网络。我们将重点讲解如何基于声学特征和机器学习模型构建说话人识别系统，特别关注使用深度学习的现代说话人识别，包括推理逻辑、损失函数和神经网络拓扑等不同选项。 此外，我们还会讨论数据处理技术，如数据清理、数据增强和数据融合。为了帮助你真正掌握本课程介绍的主题，我们将提供大量的实践操作和编码示例，并包括一个最终项目，引导你从零开始构建自己的说话人识别系统。如果你是对人工智能或信号处理感兴趣的大学生，或者是与相关技术工作的软件工程师、系统架构师或产品经理，那么本课程绝对适合你！
This course is an introduction to speaker recognition techniques.Speaker recognition lies in the intersection of audio processing, biometrics, and machine learning, and has various applications. You can find the application of speaker recognition on your smart phones, smart home devices, and various commercial services.In this course, we will start with an introduction to the history of speaker recognition techniques, to see how it evolved from simple human efforts to modern deep learning based intelligent systems.We will cover the basics of acoustics, perception, audio processing, signal processing, and feature extraction, so you don't need a background in these domains. We will also have an introduction of popular machine learning approaches, such as Gaussian mixture models, support vector machines, factor analysis, and neural networks.We will focus on how to build speaker recognition systems based on acoustic features and machine learning models, with an emphasis on modern speaker recognition with deep learning, such as the different options for inference logic, loss function, and neural network topologies.We will also talk about data processing techniques such as data cleansing, data augmentation, and data fusion.We included lots of hands-on practices and coding examples for you to really master the topics introduced in this course, and a final project to guide you through building your own speaker recognition system from scratch.If you are a college student interested in AI or signal processing, or a software engineer, system architect or product manager working with related technologies, then this course is definitely for you!
