机器学习在语音识别中的应用 -计算机科学与技术专业

摘要

随着信息技术的迅猛发展，语音识别技术在人机交互、智能设备等领域展现出广阔的应用前景。机器学习算法为提升语音识别性能提供了新的思路和方法。本研究旨在探讨机器学习在语音识别中的应用，通过对比分析传统语音识别技术和基于机器学习的语音识别技术，揭示机器学习在该领域的优势与潜力。研究采用深度神经网络、卷积神经网络和支持向量机等典型机器学习算法构建语音识别模型，利用大规模语音数据集进行训练和测试。实验结果表明，基于机器学习的语音识别系统在准确率、鲁棒性等方面较传统方法有显著提升，特别是在复杂环境下的语音识别效果更为突出。创新点在于将迁移学习引入语音识别领域，有效解决了小样本情况下模型训练不足的问题，同时提出一种融合多特征的语音识别框架，提高了对不同发音习惯的适应能力。本研究不仅验证了机器学习在语音识别中的有效性，还为后续研究提供了新的方向和思路，推动了语音识别技术向着更加智能化、个性化的方向发展。

关键词：机器学习语音识别深度神经网络

Abstract

With the rapid development of information technology, speech recognition technology has demonstrated broad application prospects in human-computer interaction and intelligent devices. Machine learning algorithms have provided new approaches and methods to enhance the performance of speech recognition. This study aims to explore the application of machine learning in speech recognition by comparing traditional speech recognition technologies with those based on machine learning, thereby revealing the advantages and potential of machine learning in this field. The research employs typical machine learning algorithms such as deep neural networks, convolutional neural networks, and support vector machines to construct speech recognition models, which are trained and tested using large-scale speech datasets. Experimental results indicate that machine-learning-based speech recognition systems exhibit significant improvements over traditional methods in terms of accuracy and robustness, particularly in complex environments. An innovation of this study lies in introducing transfer learning into the field of speech recognition, effectively addressing the issue of insufficient model training under small sample conditions. Additionally, a multi-feature fusion speech recognition fr amework is proposed, enhancing adaptability to different pronunciation habits. This research not only verifies the effectiveness of machine learning in speech recognition but also provides new directions and ideas for future studies, promoting the development of speech recognition technology towards greater intelligence and personalization.

Keyword:Machine Learning Speech Recognition Deep Neural Network

1绪论 1

1.1研究背景与意义 1

1.2国内外研究现状 1

1.3本文研究方法 1

2机器学习算法在语音识别中的选择 2

2.1常用机器学习算法概述 2

2.2算法性能对比分析 2

2.3针对语音识别的算法优化 3

3特征提取与表示学习 4

3.1传统特征提取方法 4

3.2深度学习特征表示 4