JP5162697B2 - 情報検索手法による統一化されたタスク依存の言語モデルの生成 - Google Patents
情報検索手法による統一化されたタスク依存の言語モデルの生成 Download PDFInfo
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- 238000000034 method Methods 0.000 title claims abstract description 61
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- G—PHYSICS
- G10—MUSICAL INSTRUMENTS; ACOUSTICS
- G10L—SPEECH ANALYSIS TECHNIQUES OR SPEECH SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING TECHNIQUES; SPEECH OR AUDIO CODING OR DECODING
- G10L15/00—Speech recognition
- G10L15/08—Speech classification or search
- G10L15/18—Speech classification or search using natural language modelling
- G10L15/183—Speech classification or search using natural language modelling using context dependencies, e.g. language models
- G10L15/19—Grammatical context, e.g. disambiguation of the recognition hypotheses based on word sequence rules
- G10L15/193—Formal grammars, e.g. finite state automata, context free grammars or word networks
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- G—PHYSICS
- G10—MUSICAL INSTRUMENTS; ACOUSTICS
- G10L—SPEECH ANALYSIS TECHNIQUES OR SPEECH SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING TECHNIQUES; SPEECH OR AUDIO CODING OR DECODING
- G10L15/00—Speech recognition
- G10L15/08—Speech classification or search
- G10L15/18—Speech classification or search using natural language modelling
- G10L15/1815—Semantic context, e.g. disambiguation of the recognition hypotheses based on word meaning
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- G—PHYSICS
- G10—MUSICAL INSTRUMENTS; ACOUSTICS
- G10L—SPEECH ANALYSIS TECHNIQUES OR SPEECH SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING TECHNIQUES; SPEECH OR AUDIO CODING OR DECODING
- G10L15/00—Speech recognition
- G10L15/08—Speech classification or search
- G10L15/18—Speech classification or search using natural language modelling
- G10L15/183—Speech classification or search using natural language modelling using context dependencies, e.g. language models
- G10L15/19—Grammatical context, e.g. disambiguation of the recognition hypotheses based on word sequence rules
- G10L15/197—Probabilistic grammars, e.g. word n-grams
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Description
w1は、このシーケンス中において単語wのn−1個前に位置する単語;
w2は、単語wのn−2個前に位置する単語;
w(n−1)は、単語wの1個前に位置する単語;
また、単語シーケンスの確率は、その履歴を与えられた各単語の確率の乗法演算に基づいて定められる。したがって、単語シーケンス(w1・・wm)の確率は、以下のように表される。
Claims (6)
- 言語処理システムのための言語モデルを構築するための方法を実行するためのコンピュータ読み取り可能な命令を格納したコンピュータ読み取り可能な媒体において、前記方法は、
選択されたアプリケーションの意味上または構文上の概念を表すノンターミナルトークンを備えた複数の文脈自由文法にアクセスするステップと、
前記複数の文脈自由文法から単語フレーズを生成するステップと、
該単語フレーズの少なくとも一つからクエリを生成するステップと、
当該生成されたクエリに基づいてタスク独立のコーパスを照会することにより、前記タスク独立のコーパスにおける関連するテキストを特定するステップと、
当該特定されたテキストを用いて言語モデルを構築するステップと
を備えたことを特徴とするコンピュータ読み取り可能な媒体。 - 前記言語モデルを構築するステップは、Nグラム言語モデルを構築するステップを備えたことを特徴とする請求項1に記載のコンピュータ読み取り可能な媒体。
- 前記方法は、
前記複数の文脈自由文法によって前記タスク独立のコーパスの前記特定されたテキストをパージングして前記意味上または構文上の概念の各々の単語と一致する単語を特定するステップと、
当該特定された単語の各々を、前記特定された単語に対応する文脈自由文法によって定められたノンターミナルトークンで置き換えるステップとをさらに備え、
前記Nグラム言語モデルを構築するステップは、当該置き換えられたノンターミナルトークンを有するNグラムモデルを構築するステップを備えたことを特徴とする請求項2に記載のコンピュータ読み取り可能な媒体。 - 言語処理システムのための言語モデルを構築するための方法を実行するためのコンピュータ読み取り可能な命令を格納したコンピュータ読み取り可能な媒体において、前記方法は、
選択されたアプリケーションの意味上または構文上の概念を表すノンターミナルトークンを備えた複数の文脈自由文法にアクセスするステップと、
前記複数の文脈自由文法から単語フレーズを生成するステップと、
該単語フレーズから第1のNグラム言語モデルを構築するステップと、
前記単語フレーズの少なくとも一つから情報検索クエリを生成するステップと、
当該生成されたクエリに基づいてタスク独立のコーパスを照会することにより、前記タスク独立のコーパスにおける関連するテキストを特定するステップと、
当該特定されたテキストから第2のNグラム言語モデルを構築するステップと、
前記第1のNグラム言語モデルと前記第2の言語モデルとを組み合わせて第3のNグラム言語モデルを形成するステップと
を備えたことを特徴とするコンピュータ読み取り可能な媒体。 - 前記第2のNグラム言語モデルを構築するステップは、前記特定されたテキストのみを用いるステップを含むことを特徴とする請求項4に記載のコンピュータ読み取り可能な媒体。
- 前記方法は、
前記複数の文脈自由文法によって前記タスク独立のコーパスをパージングして前記意味上または構文上の概念の各々の単語と一致する単語を特定するステップと、
当該特定された単語の各々を、前記特定された単語に対応するノンターミナルトークンで置き換えるステップとをさらに備え、
前記単語フレーズは、ノンターミナルトークンを含み、
前記第1のNグラム言語モデルを構築するステップは、当該置き換えられたノンターミナルトークンを有するNグラムモデルを構築するステップを備えたことを特徴とする請求項4に記載のコンピュータ読み取り可能な媒体。
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US09/585,298 US7031908B1 (en) | 2000-06-01 | 2000-06-01 | Creating a language model for a language processing system |
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EP (1) | EP1290676B1 (ja) |
JP (2) | JP5099953B2 (ja) |
AT (1) | ATE343198T1 (ja) |
AU (1) | AU2001274936A1 (ja) |
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JP2003535410A (ja) | 2003-11-25 |
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JP5099953B2 (ja) | 2012-12-19 |
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WO2001093246A3 (en) | 2002-09-12 |
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