然后，采用基于SVM的分类器，设计与实现音频分类模块；
Then, we design and implement an audio classification module based on SVM.
音频分类技术是解决这一问题的有效方法，是音频内容结构化的基础。
Audio classification technology is the major technology to solve this problem and it is the basis of audio content extraction.
音频分类与分割技术是解决这一问题的关键技术，是音频结构化的基础。
Audio classification and segmentation are key technologies for solving such problems, and are the basis of audio structured.
音频特征提取是音频分类的基础，而音频分类又是基于内容的音频检索的关键。
Feature extraction is the foundation of audio classification, while audio classification is a key of content based audio retrieval.
体育视频中的声音鲁棒性比较好，有监督的音频分类可以做到针对一种比赛项目的通用性。
The audio is robust and supervised audio classification is general in the same type sports video.
实验结果显示，基于SVM的音频分类算法分类效果良好，平滑处理后的音频分割结果比较准确。
Experiment results show that SVM performs very well for au - dio classification and segmentation accuracy is good with the proposed three smooth rules.
用于人形机器人的实时多通道降噪方法使机器人能够在实际应用中精确地进行后续的音频分类或语音识别。
A real time, multichannel, humanoid robot ready noise reduction method makes practical precise audio classification and speech recognition possible.
本文对现有的音频分类技术及其应用进行充分研究，设计与实现了基于支持向量机的音频分类模块，应用于多个多媒体应用系统中。
In this paper, we study the existing audio classification methods. We design and implement a SVM-based audio classification module, and apply to many multimedia application systems.
在音频这个频道的首页上以按分类(漫画，游戏，健康等)展示出最流行的音频节目。
The podcasting homepage will list the most popular podcasts by category (comedy, gaming, health, etc.).
所有在场景中播放的声音，都可以被放到一个或者多个音频混合器中，这些音频混合器将自动对这些音频进行分类，并将所有的调整与效果应用到这些混合的音源中。
All the sounds playing in a scene can be routed into one or more AudioMixer which will categorise them and apply all sorts of modifications and effects to the mix of those sounds.
在此基础上主要就镜头分割、关键帧选取、音频特征分类以及视频中文字区域的检测和分割提出了相应改进的算法。
Further it mainly aims at the segment of shot, selection of key frame, classify of audio characteristic and detection of caption-region in video and presents corresponding improved approach.
提出了一种利用训练数据的类别信息改善分类效果的音频特征提取方法。
An audio feature extraction method which can improve classification rate by utilizing the class information is proposed in this paper.
提出了一种利用“段分类”的DCT域自适应音频水印方法，可应用于音频信息的版权保护。
This paper presents an audio watermarking method in DCT based on "segment classification", which can be used to copyright protection of audio information.
实验表明，盲分类器可以实现MIDI音频三种隐写方法的有效检测。
Experiments show that the blind classifier can detect three methods steganography of MIDI audio effectively.
根据音频段的分类效果，不同强度的水印分量被嵌入到不同音频段中的部分DCT低频系数中。
Components of watermarking with different strength are embedded into the parts of low frequency DCT parameters in different audio segment according to the classification results. T...
根据音频段的分类效果，不同强度的水印分量被嵌入到不同音频段中的部分DCT低频系数中。
Components of watermarking with different strength are embedded into the parts of low frequency DCT parameters in different audio segment according to the...
根据音频段的分类效果，不同强度的水印分量被嵌入到不同音频段中的部分DCT低频系数中。
Components of watermarking with different strength are embedded into the parts of low frequency DCT parameters in different audio segment according to the...
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