JP6746292B2 - 言語モデル学習方法及び装置、言語認識方法及び装置 - Google Patents
言語モデル学習方法及び装置、言語認識方法及び装置 Download PDFInfo
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Description
110:学習データ前処理部
120:言語モデル学習部
122:学習処理部
124:制御部
126:算出処理部
128:エラー算出処理
300:言語認識装置
310:入力データ前処理部
320:言語モデルデータベース
330:入力データ認識部
Claims (12)
- 言語モデル学習装置の作動方法であって、前記言語モデル学習装置はコンピュータによって実装され、
前記コンピュータが、単語を含んでいる学習データである入力データから、順方向推定のための第1学習特徴ベクトル列及び逆方向推定のための第2学習特徴ベクトル列を生成するステップと、
前記コンピュータが、前記第1学習特徴ベクトル列に基づいて神経網の順方向推定を行い、かつ、前記第2学習特徴ベクトル列に基づいて前記神経網の逆方向推定を行うステップと、
前記コンピュータが、前記順方向推定の結果及び前記逆方向推定の結果に基づいて、言語モデルを学習させるステップと、
を含み、
前記第1学習特徴ベクトル列は入力データの単語ベクトル列の順方向で開始し、かつ、前記第2学習特徴ベクトル列は、前記単語ベクトル列の逆方向で開始し、
前記神経網は、前記順方向推定のための第1隠れレイヤおよび前記逆方向推定のための第2隠れレイヤを含み、前記第1隠れレイヤは、前記第2隠れレイヤと分離しており、かつ、
前記第1隠れレイヤおよび前記第2隠れレイヤそれぞれは、階層構造を有している、
方法。 - 前記生成するステップは、
前記コンピュータが、前記学習データを単語ベクトル列に変換するステップと、
前記コンピュータが、前記単語ベクトル列の順方向に開始する前記第1学習特徴ベクトル列、及び前記単語ベクトル列の逆方向に開始する前記第2学習特徴ベクトル列を生成するステップと、
を含む、請求項1に記載の方法。 - 前記順方向推定は、前記コンピュータが、前記学習データに含まれた第1単語の次に連結する単語を推定するステップを含み、
前記逆方向推定は、前記コンピュータが、前記学習データに含まれた第2単語の以前に連結した単語を推定するステップを含む、
請求項1または2に記載の方法。 - 前記学習させるステップは、
前記コンピュータが、前記順方向推定の結果及び前記逆方向推定の結果に基づいて前記学習データと前記神経網の出力データとの間のエラー値を算出するステップと、
前記コンピュータが、前記エラー値に基づいて前記神経網に含まれた人工ニューロン間の接続加重値をアップデートするステップと、
を含む、請求項1乃至3いずれか一項に記載の方法。 - 前記言語モデルは、BLSTM(Bidirectional Long Short−Term Memory)構造の再帰神経網に基づく、
請求項1乃至4いずれか一項に記載の方法。 - 前記BLSTM構造の再帰神経網は、以前時間区間で出力された値を次の時間区間まで保持するメモリブロックを含む、
請求項5に記載の方法。 - 前記学習データは、音声データ及び筆跡データのうち少なくとも1つに構成された順次的データを含む、
請求項1乃至4いずれか一項に記載の方法。 - 請求項1乃至7いずれか一項に記載の方法を実行するためのプログラムが記録されたコンピュータで読み出し可能な記録媒体。
- コンピュータによって実装される言語モデル学習装置であって、
前記コンピュータによって、単語を含んでいる学習データである入力データから、順方向推定のための第1学習特徴ベクトル列及び逆方向推定のための第2学習特徴ベクトル列を生成する、ように構成されている学習データ前処理部と、
前記コンピュータに、前記第1学習特徴ベクトル列及び前記第2学習特徴ベクトル列に基づいて神経網ベースの言語モデルを学習させ、前記第1学習特徴ベクトル列について前記神経網の順方向推定を行い、かつ、前記第2学習特徴ベクトル列について前記神経網の逆方向推定を行うように構成されている言語モデル学習部と、
を含み、
前記第1学習特徴ベクトル列は入力データの単語ベクトル列の順方向で開始し、かつ、前記第2学習特徴ベクトル列は、前記単語ベクトル列の逆方向で開始し、
前記神経網は、前記順方向推定のための第1隠れレイヤおよび前記逆方向推定のための第2隠れレイヤを含み、前記第1隠れレイヤは、前記第2隠れレイヤと分離しており、かつ、
前記第1隠れレイヤおよび前記第2隠れレイヤそれぞれは、階層構造を有している、
言語モデル学習装置。 - 前記言語モデル学習部は、前記順方向推定の結果及び前記逆方向推定の結果に基づいて、前記コンピュータに前記言語モデルを学習させる、
請求項9に記載の言語モデル学習装置。 - 前記言語モデル学習部は、順方向推定結果及び逆方向推定結果に基づいて、前記コンピュータによって、学習データと出力データとの間のエラー値を算出し、前記エラー値に基づいて前記神経網に含まれた人工ニューロン間の接続加重値をアップデートする、
請求項9または10に記載の言語モデル学習装置。 - 前記学習データ前処理部は、前記コンピュータによって、前記学習データを単語ベクトル列に変換し、前記単語ベクトル列の順方向に開始する前記第1学習特徴ベクトル列、及び前記単語ベクトル列の逆方向に開始する前記第2学習特徴ベクトル列を生成する、
請求項9乃至11いずれか一項に記載の言語モデル学習装置。
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