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Description: 语音质量客观评估，IS测度， Itakura-Saito (IS) Objective Speech Quality Measure-objective speech quality assessment, IS measure, Itakura - Saito (IS) Objective Speech Quality Measure
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Size: 1902 |
Author: gogodq |
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Description: 语音质量客观评估，IS测度， Itakura-Saito (IS) Objective Speech Quality Measure-objective speech quality assessment, IS measure, Itakura- Saito (IS) Objective Speech Quality Measure
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Size: 2048 |
Author: gogodq |
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Description: Itakura-Saito (IS) Objective Speech Quality Measure
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Size: 1024 |
Author: Mehrtash |
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Description: Log Likelihood Ratio (LLR) Objective Speech Quality Measure
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Size: 1024 |
Author: Mehrtash |
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Description: 声音处理的MATLAB程序：DISTISPF -calculates the Itakura-Saito spectral distance between power spectra
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Size: 2048 |
Author: 苏 |
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Description: 文献“Majorization-minimization algorithm for smooth Itakura-Saito nonnegative matrix factorization”的matlab仿真源码-Matlab simulation source literature Majorization-minimization algorithm for smooth Itakura-Saito nonnegative matrix factorization "
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Size: 2198528 |
Author: 陈为 |
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Description: Bayesian estimator based on the modified Itakura-Saito for speech enhancement
Implements the Bayesian estimator based on the modified Itakura-Saito
Noise magnitude calculations - assuming that the first 6 frames is noise/silence
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Size: 2048 |
Author: sami |
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Description: comp_snr.m总体和节段SNR，comp_wss.m加权频谱斜率度量，omp_llr.m似然比测量，comp_is.m板仓斋藤措施，comp_cep.m倒谱距离测量，addnoise_asl.m 基于活动语音水平以指定的SNR将噪声添加到干净的信号
-comp_snr.m Overall and segmental SNR，comp_wss.m Weighted-spectral slope metric，comp_llr.m Likelihood-ratio measure ，comp_is.m Itakura-Saito measure，comp_cep.m Cepstral distance measure，addnoise_asl.m Adds noise to the clean signal at specified SNR based on active speech level.
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Size: 178176 |
Author: zhang |
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Description: Dynamic Time Warping（DTW）诞生有一定的历史了（日本学者Itakura提出），它出现的目的也比较单纯，是一种衡量两个长度不同的时间序列的相似度的方法。应用也比较广，主要是在模板匹配中，比如说用在孤立词语音识别（识别两段语音是否表示同一个单词），手势识别，数据挖掘和信息检索等中。(The birth of Dynamic Time Warping (DTW) has a certain history (Itakura, a Japanese scholar), and its purpose is relatively simple. It is a method of measuring the similarity of two different time series of different lengths. It is widely used, mainly in template matching, for example, in isolated word speech recognition (whether two segments of speech represent the same word), hand gesture recognition, data mining and information retrieval.)
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Size: 1024 |
Author: cxj01
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