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<iframe name="ngram_chart" src="" width=900 height=500 marginwidth=0 marginheight=0hspace=0 vspace=0 frameborder=0 scrolling=no></iframe> Part-of-speech tags cook_VERB, _DET_ President _PROPN_ Wildcards King of *, best *_NOUN Inflections shook_INF drive_VERB_INF Arithmetic compositions (color /(color + colour)) Corpus selection I want:eng_2019, I want:eng_2009
自然言語処理の研究で役立つツールを集めてみました。音声認識CMU Sphinx: 広く利用されている音声認識プログラム。 Juicer: 重み付き有限状態トランスデューサを利用した音声認識デコーダ。 Julius:音声認識システムの開発・研究のためのオープンソースの高性能な汎用大語彙連続音声認識エンジン。 言語モデルIRSTLM: 言語モデルの学習・格納ツール。 kenlm: メモリ効率とスピードを重視した言語モデル保持ツール。 Kylm: 重み付き有限状態トランスデューサーの出力や未知語の文字ベースモデル化などの機能が揃っている言語モデルツールキット。Javaで実装。 RandLM: 乱択データ構造であるBloom Filterを用いることで、膨大な言語モデルを少ないメモリで保持するツールキット。 SRILM: 効率的なn-gram言語モデルツールキット。様々な平滑化手法（Knese
SVMperf Support VectorMachine for Multivariate Performance Measures Author: Thorsten Joachims <thorsten@joachims.org> Cornell University Department of Computer Science Version: 3.00 Date: 07.09.2009 Overview SVMperf is an implementation of the Support VectorMachine (SVM) formulation for optimizing multivariate performance measures described in [Joachims, 2005]. Furthermore, SVMperf implements th
SVMmulticlass Multi-Class Support VectorMachine Author: Thorsten Joachims <thorsten@joachims.org> Cornell University Department of Computer Science Version: 2.20 Date: 14.08.2008 Overview SVMmulticlass uses the multi-class formulation described in [1], but optimizesit with an algorithm that is very fast in thelinear case. For a training set (x1,y1) ... (xn,yn) with labels yi in [1..k],it finds
Discover the next evolution of MuleSoft, announced at Connect:AI. Catch up on the highlights. Sincejoining MuleSoft in 2013, ProgrammableWeb has sought to bring awareness to the impactAPIs can have on modern businesses. Nearly a decade laterit has undoubtedly played a role in helping the wider market understand the power ofAPIs. As part of theSalesforce family, MuleSoft is expanding our focus
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