Search Results for "hmm c++"
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Showing 11 open source projects for "hmm c++"
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hts_engine is software to synthesize speech waveform from HMMs trained by the HMM-based speech synthesis system (HTS). This software is released under the Modified BSD license.
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Sinsy
HMM-based singing voice synthesis system
Sinsy is an HMM-based singing voice synthesis system. This software is released under the Modified BSD license. -
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The General Hidden Markov Model Library (GHMM) is a C library with additional Python bindings implementing a wide range of types of Hidden Markov Models and algorithms: discrete, continous emissions, basic training, HMM clustering, HMM mixtures.
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MetaDomain
Protein domain classification for short sequences
MetaDomain is a protein domain classification tool designed for very short next-generation sequencing reads. It achieves better sensitivity and low false positive rate compared with the state-of-the-art profile hidden Markov model (profile HMM) alignment tool in identifying encoded domains from short sequences. -
Empower decisions with IBM SPSS Statistics.IBM SPSS Statistics software is used by a variety of customers to solve industry-specific business issues to drive quality decision-making. Advanced statistical procedures and visualization can provide a robust, user friendly and an integrated platform to understand your data and solve complex business and research problems
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HPeak
A HMM-based algorithm for defining enriched regions from ChIP-seq data
HPeak is a hidden Markov model-based approach that can accurately pinpoint regions to where significantly more sequence reads map. Testing on real data shows that these regions are indeed highly enriched by the right protein binding sites. Command (single-end): perl /compbio/software/HPeak3/HPeak.pl -sp HUMAN/MOUSE -format BED -t TREATMENT.inp -c CONTROL.inp -n OUTPUTPREFIX -fmin 100 -fmax 300 -r 36 -ann -wig -seq -interfiles Command (pair-end): perl /compbio/software/HPeak3/HPeak.pl -sp... -
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The AK toolkit is another kit for building and use Hidden Markov Models (HMMs). Originally developed for handwritten text recognition (HTR) using Bernoulli HMMs, it also implements diagonal Gaussians and can be used for any other purpose.
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CvHMM
Discrete Hidden Markov Models based on OpenCV
This project (CvHMM) is an implementation of discrete Hidden Markov Models (HMM) based on OpenCV. It is simple to understand and simple to use. The Zip file contains one header for the implementation and one main.cpp file for a demonstration of how it works. Hope it becomes useful for your projects. -
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LibNebular is C++ Linux library for uniform image file manipulation as String key-value pairs (with sometimes BLOB values) where different file types are intruduced through DL (".so") libraries. Includes BMP and JPEG plugins. Can easily be ported.
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MeCab is a fast and customizable Japanese morphological analyzer. MeCab is designed for generic purpose and applied to variety of NLP tasks, such as Kana-Kanji conversion. MeCab provides parameter estimation functionalities based on CRFs and HMM
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Cloud-based observability solution that helps businesses track and manage workload and performance on a unified dashboard.Monitor everything you run in your cloud without compromising on cost, granularity, or scale. groundcover is a full stack cloud-native APM platform designed to make observability effortless so that you can focus on building world-class products. By leveraging our proprietary sensor, groundcover unlocks unprecedented granularity on all your applications, eliminating the need for costly code changes and development cycles to ensure monitoring continuity.
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Hidden Markov Models (HMM) are a Pattern Recognition Metaheuristic. JHMMSim lets you to train and test a HMM with a friendly Java/Swing GUI. Also, JHMMSim lets you to generate a C++ code with a trained HMM, so you can use it in your own applications.
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This is a project to create a compiler that converts grammars written in SRGS standard (http://www.w3.org/TR/speech-grammar/) to a graph understandable by HMM based ASR engines. Check srgs-parser.sf.net
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