Description: 隐马尔科夫模型对文本信息进行抽取利用MATLAB实现-Hidden Markov Model for text information extraction realize the use of MATLAB Platform: |
Size: 34816 |
Author:longge1998 |
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Description: 隐马尔科夫模型对文本信息进行抽取利用C＋＋实现-Hidden Markov Model for text information extraction using C realize Platform: |
Size: 15360 |
Author:longge1998 |
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Description: 基于最大熵的隐马尔可夫模型文本信息抽取,林亚平!刘云中!周顺先!陈治平!蔡立军"湖南大学计算机与通信学院!湖南长沙#$％％&-Based on Maximum Entropy of Hidden Markov Model Text Information Extraction, Ya-Ping Lin! Liu in!廃?first! Chen Zhiping! Cai-jun, Platform: |
Size: 171008 |
Author:刘鹏飞 |
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Description: 自己编写的语音识别程序-基于隐马尔可夫模型的语音识别-I have written the speech recognition program- Based on Hidden Markov Model Speech Recognition Platform: |
Size: 5120 |
Author:小苗 |
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Description: CRF1.2，条件随机场软件包，很好用很流行的一个文本分类软件，可以用于自然 语言的处理，标签，分类，词性发现，用户只需要着重构造特征函数既可以，实验结果和应用表明crf要优于隐马尔科夫模型。实现环境为java语言。-CRF1.2, conditions package with the airport, very good very popular with a text classification software, can be used in natural language processing, labeling, sorting, part of speech found that users only need to focus on structural characteristic function can, experimental results and applications show that the CRF is superior to Hidden Markov Model. Environment for the realization of java language. Platform: |
Size: 2252800 |
Author:陈先开 |
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Description: TEXT SEGMENTATION AND TOPIC TRACKING ON BROADCAST NEWS VIA A HIDDEN MARKOV MODEL APPROACH Platform: |
Size: 92160 |
Author:khanhhoa |
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Description: 4篇介绍隐马尔可夫模型、ARMA倒谱、基于矢量量化改进算法的说话人识别、与文本无关的说话人识别研究的论文，对需要的还是有帮助的-4 introduced the hidden Markov model, ARMA cepstrum, based on vector quantization algorithm for speaker recognition improved, and text-independent speaker recognition research papers, or in need of help Platform: |
Size: 1852416 |
Author:lanyuna |
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Description: This paper describes a technique for automatic recognition of off-line printed Arabic text using Hidden Markov Models. In this work different sizes of overlapping and non-overlapping hierarchical windows are used to generate 16 features from each vertical sliding strip. Eight different Arabic fonts were used for testing (viz. Arial, Tahoma, Akhbar, Thuluth, Naskh, Simplified Arabic, Andalus Platform: |
Size: 693248 |
Author:ammar |
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Description: 基于隐马尔科夫模型的文本信息提取，压缩包中带有源码和相关资料-Hidden Markov Model based text information extraction, compressed packets with source code and related information Platform: |
Size: 2990080 |
Author:李丽 |
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Description: Finally, probability analysis, based on the chosen database, is performed and
judgment whether the person is recognized is pronounced. Two different modeling
techniques can be suggested for purposes of person identification or verification. The
approach based on Hidden Markov Speaker Models (HMMs) with the mixtures of
Gaussian distribution is text-dependent one. For this technology a speaker is
described by a set of HMMs, constructing the set of speech groups spoken by that
person. The speech groups may be phonemes or words [7]. The text-independent
technology is rested upon Gaussian Mixture Speaker Models. For this technology
each speaker is defined by only one model describing all utterances of that person.
Identification in the range of both approaches is executed by evaluation of maximum
a posteriori probability [7]. Platform: |
Size: 3019776 |
Author:rasul |
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Description: Fox & Pigeon Laboratory 发布一款基于隐马尔可夫模型的英语语音合成软件（HMM based English Text-To-Speech, TTS）：FoxPigeonTTS alpha版。
近年来，基于HMM的语音合成系统得到广泛的重视和应用。我们实验室实现的基于HMM的语音合成系统基本不需要任何语言学知识指导系统训练，构建时间短，构建过程基本不需要人工干预，而由于系统属于参数化合成方法，系统的合成结果灵活多变，可以很容易的应用于多个发音人，多种发音风格，多种情感表达的需求中。
我们的实验室实现的英语语音合成技术音质好，自然度高，可懂度高。并且整个系统基于C开发，可以很方便的移植到其他移动平台。
下一步我们会开发中文语音合成技术，以及在 提高合成语音的自然度、丰富合成语音的表现力、降低语音合成技术的复杂度、多语种文语合成方面做进一步的研究。-Fox & Pigeon Laboratory released a hidden Markov model based on the English speech synthesis software (HMM based English Text-To-Speech, TTS): FoxPigeonTTS alpha version.
In recent years, HMM-based speech synthesis system has been widely appreciated and applications. Our laboratory implemented HMM-based speech synthesis system does not require any basic knowledge of linguistics training guidance system, build time is short, the basic building process does not require human intervention, and because the system belongs parametric synthesis, synthesis of the results of the system flexible , can easily be applied to multiple pronunciations who demand a variety of pronunciation styles in a variety of emotional expression.
Our laboratory English speech synthesis technology to achieve good sound quality, natural high, high intelligibility. And the entire system is based on C development, can be easily ported to other mobile platforms.
Next, we will develop Chinese speech synthesis tech Platform: |
Size: 3270656 |
Author:Shi |
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Description: In this paper, we figure out the use of appended jitter and shimmer speech features for closed set text
independent speaker identification system. Jitter and shimmer features are extracted from the
fundamental frequency contour and added to baseline spectral features, specifically Mel-frequency
Cepstral Coefficients (MFCCs) for human speech and MFCC-GC which integrate the Gammachirp
filterbank instead of the Mel scale. Hidden Markov Models (HMMs) with Gaussian Mixture Models
(GMMs) state distributions are used for classification. Our approach achieves substantial performance
improvement in a speaker identification task compared with a state-of-the-art robust front-end in a
clean condition. Platform: |
Size: 256000 |
Author:mansouri |
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Search - hidden markov text