|
所在平台: Udemy |
课程主页: https://www.udemy.com/course/diarization/
课程评论：没有评论
Coursera 课程：说话人日志教程 本课程是一门关于说话人日志（Speaker Diarization）技术的教程。说话人日志是语音处理领域的一个高级主题，它解决了“谁在何时说话”以及“谁说了什么”的问题。该技术与语音活动检测、说话人识别、自动语音识别、语音分离、统计学和深度学习等多种技术紧密相关，并在自动会议转录生成、病历分析、媒体索引与检索以及二阶段语音识别等众多场景中具有广泛的应用。 课程内容涵盖： 1. **基础概念与应用**：首先介绍说话人日志的基本概念及其应用场景。 2. **评分与评估指标**：讲解说话人日志的评估方法和常用指标。 3. **无监督说话人日志方法**： * 介绍常用的模块化框架。 * 深入探讨聚类算法，重点关注谱聚类及其扩展。 * 分析聚类算法存在的问题。 4. **监督说话人日志方法**： * 详细介绍四种监督学习方法：UIS-RNN、PIT/EEND、TS-VAD 和 DNC。 5. **挑战与未来方向**：探讨说话人日志领域当前存在的挑战和未来的研究方向。 此外，课程还提供： * **学术会议视频**：收录来自 ICASSP 和 SLT 等顶级语音会议的讲师视频，作为补充学习材料。 * **随堂测验**：每节课后设有小测验，帮助巩固学习内容。 * **实践练习与项目**：提供各种编码实践和项目，熟悉 SCTK、pyannote-metrics、pyannote-audio 和 uisrnn 等常用工具包。 **目标学员**：适用于从事音频和语音处理工作的学生、研究人员、开发人员或产品经理。
This course is a tutorial on speaker diarization techniques.Speaker diarization is an advanced topic in speech processing. It solves the problem "who spoke when", or "who spoke what". It is highly relevant with many other techniques, such as voice activity detection, speaker recognition, automatic speech recognition, speech separation, statistics, and deep learning. It has found various applications in numerous scenarios, such as automatic meeting transcript generation, medical record analysis, media indexing and retrieval, and second pass speech recognition.In this course, we will first go through the basic concepts and applications of speaker diarization, followed by the scoring and metrics. Then we will introduce the unsupervised methods in speaker diarization, starting with the commonly used modularized framework, followed by an introduction to clustering algorithms, with a focus on spectral clustering and its extensions. Next, we will talk about the problems with clustering algorithms, and introduce the supervised methods in speaker diarization. We will mainly talk about 4 supervised speaker diarization approaches, i.e. UIS-RNN, PIT/EEND, TS-VAD, and DNC. Finally, we will talk about the challenges and future research directions in speaker diarization.For those who want to dive deep in speaker diarization, we also include video lectures from top speech conferences such as ICASSP and SLT by the instructors as additional learning materials.Apart from the lecture videos, we have included small quizzes after each lecture to help you better understand the topics we have covered in the lecture.Also, speaker diarization is a very practical skill. Thus we have carefully prepared various coding practices and projects, to get you familiar with the most popular toolkits which are used by various researchers and scientists, including SCTK, pyannote-metrics, pyannote-audio and uisrnn.This course would be a great fit for students, researchers, developers, or product managers who work on audio and speech processing.
