基于Python+WaveNet+MFCC+Tensorflow智能方言分类-深度学习算法应用(含全部工程源码)

上传者: 31136513 | 上传时间: 2025-01-13 20:25:03 | 文件大小: 16.4MB | 文件类型: RAR
1.本项目以科大讯飞提供的数据集为基础,通过特征筛选和提取的过程,选用WaveNet模型进行训练。旨在通过语音的梅尔频率倒谱系数(MFCC)特征,建立方言和相应类别之间的映射关系,解决方言分类问题。 2.项目运行环境包括:Python环境、TensorFlow环境、JupyterNotebook环境、PyCharm环境。 3.项目包括4个模块:数据预处理、模型构建、模型训练及保存、模型生成。数据集网址为:challenge.xfyun.cn,向用户免费提供了3种方言(长沙话、南昌话、上海话),每种方言包括30人,每人200条数据,共计18000条训练数据,以及10人、每人50条,共计1500条验证数据;WaveNet模型是一种序列生成器,用于语音建模,在语音合成的声学建模中,可以直接学习采样值序列的映射,通过先前的信号序列预测下一个时刻点值的深度神经网络模型,具有自回归的特点;通过Adam()方法进行梯度下降,动态调整每个参数的学习率,进行模型参数优化 4.项目博客:https://blog.csdn.net/qq_31136513/article/details/134832627

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