Description: 采用bic准则的音频流分割程序，能够准确找出不同音频种类的分界点位置，如音乐和语音。-adopted guidelines streaming audio segmentation procedures to accurately identify different types of audio demarcation point position, as music and voice. Platform: |
Size: 2595 |
Author:gqy |
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Description: 采用bic准则的音频流分割程序，能够准确找出不同音频种类的分界点位置，如音乐和语音。-adopted guidelines streaming audio segmentation procedures to accurately identify different types of audio demarcation point position, as music and voice. Platform: |
Size: 2048 |
Author: |
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Description: 语音合成与分割！很好的工具哦，可以将MP3等音频分割或者合成-Speech Synthesis and Segmentation! Oh, very good tool, you can split MP3 and other audio or synthetic Platform: |
Size: 1946624 |
Author:Jackey |
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Description: audio analysis
基本的音频处理函数 用于音频分类和分割-audio analysis of basic audio processing function for audio classification and segmentation Platform: |
Size: 39936 |
Author:Yu Gong |
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Description: YambMP4格式转换工具，能够转换MP3,PCMA,PCMU,EVRC等多种格式的音频文件，能够增加字幕，切分合并文件。是非常不错的工具-YambMP4 format conversion tool that can convert MP3, PCMA, PCMU, EVRC and many other audio file formats, can increase the subtitles, the consolidated document segmentation. Is a very good tool Platform: |
Size: 6560768 |
Author:TongSHengYou |
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Description: 边界识别，找出音频汉字与汉字的切分时间点-Boundary identification, find audio Segmentation of Chinese Characters and time Platform: |
Size: 548864 |
Author:夏至 |
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Description: 音频分割代码，实现音频特征的提取，并用几个重要的特征进行分割-Audio segmentation code, the extraction of audio features, and with a few important features to segment Platform: |
Size: 90112 |
Author:景雄 |
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Description: his a simple method for silence removal and segmentation of audio streams that contain speech. The method is based in two simple audio features (signal energy and spectral centroid). As long as the feature sequences are extracted, as thresholding approach is applied on those sequence, in order to detect the speech segment-his is a simple method for silence removal and segmentation of audio streams that contain speech. The method is based in two simple audio features (signal energy and spectral centroid). As long as the feature sequences are extracted, as thresholding approach is applied on those sequence, in order to detect the speech segment Platform: |
Size: 980992 |
Author:petr |
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Description: A Novel Efficient Approach for Audio Segmentation
a novel approach to audio segmentation
is presented. The problem of detecting audio segments’
limits is treated as a binary classification task.
Frames are classified as “segment limits” vs “nonsegment
limits”. For each audio frame a spectrogram
is computed and eight feature values are extracted from
respective frequency bands. Final decisions are taken
based on a classifier combination scheme Platform: |
Size: 225280 |
Author:kvga |
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Description: a model-free and training-free two-phase method for audio segmentation that separates monophonic heterogeneous audio files into acoustically homogeneous regions where each region contains a single sound Platform: |
Size: 150528 |
Author:kvga |
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Description: This project describes the work done on the development of an audio segmentation and classification system. Many existing works on audio classification deal with the problem of classifying known homogeneous audio segments. In this work, audio recordings are divided into acoustically similar regions and classified into basic audio types such as speech, music or silence. Audio features used in this project include Mel Frequency Cepstral Coefficients (MFCC), Zero Crossing Rate and Short Term Energy (STE). These features were extracted from audio files that were stored in a WAV format. Possible use of features, which are extracted directly from MPEG audio files, is also considered. Statistical based methods are used to segment and classify audio signals using these features. The classification methods used include the General Mixture Model (GMM) and the k- Nearest Neighbour (k-NN) algorithms. It is shown that the system implemented achieves an accuracy rate of more than 95 for discrete audio classification.-This project describes the work done on the development of an audio segmentation and classification system. Many existing works on audio classification deal with the problem of classifying known homogeneous audio segments. In this work, audio recordings are divided into acoustically similar regions and classified into basic audio types such as speech, music or silence. Audio features used in this project include Mel Frequency Cepstral Coefficients (MFCC), Zero Crossing Rate and Short Term Energy (STE). These features were extracted from audio files that were stored in a WAV format. Possible use of features, which are extracted directly from MPEG audio files, is also considered. Statistical based methods are used to segment and classify audio signals using these features. The classification methods used include the General Mixture Model (GMM) and the k- Nearest Neighbour (k-NN) algorithms. It is shown that the system implemented achieves an accuracy rate of more than 95 for discrete audio classification. Platform: |
Size: 653312 |
Author:kvga |
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Description: Watermarking embeds information into a digital signal like
audio, image, or video. Reversible image watermarking can restore the
original image without any distortion after the hidden data is extracted.
In this paper, we present a novel reversible watermarking scheme using
an interpolation technique, which can embed a large amount of covert
data into images with imperceptible modification. Different from previous
watermarking schemes, we utilize the interpolation-error, the difference
between interpolation value and corresponding pixel value Platform: |
Size: 2541568 |
Author:isclor |
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Description:
This program is the program implementing the audio Segmentation.I used a adaboost and camshift algorithm with opencv and vc++
It is the program which is suitable for the development environment with the program related to the audio merotomy. Platform: |
Size: 950272 |
Author:pattern |
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Search - audio segmentation