基于混合分类器的AMR-WB语音隐写分析方法

被引：0
|
作者：
吴彦鹏
陈明辉
曹荣鑫
孙奕
机构：
[1] 厦门市美亚柏科信息股份有限公司
来源：
通信技术 | 2020年 / 53卷 / 10期
关键词：
信息隐藏; 隐写分析; 自适应多速率宽带编码; 支持向量机; 长短期记忆模型;
D O I：
暂无
中图分类号：
TP181 [自动推理、机器学习]; TN918.4 [密码的加密与解密];
学科分类号：
摘要：
基于自适应多速率宽带语音编码的信息隐藏方法具有较强的隐蔽性和抗检测能力。为检测导谱频率矢量索引搜索中的量化索引调制,提出了一种基于校准技术和混合分类器的隐写分析方法。其中,一种基于长短期记忆模型的特征提取方法被用于提取导谱频率的关联性特征,导谱频率量化索引的概率分布则作为导谱频率的长时分布特征。以上两种特征通过校准技术处理后,被送入支持向量机中进行训练,可获得具有较高分类性能的分类器。实验结果表明,在不同嵌入率和语音长度下,所提方法均有较高的分类正确率。
引用
收藏
页码：2418 / 2424
页数：7
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