プレプリント / バージョン1

大規模言語モデルの翻訳を評価する大規模共同研究

心理尺度の人手-機械翻訳間の24比較

##article.authors##

DOI:

https://doi.org/10.51094/jxiv.2056

キーワード:

大規模言語モデル、 機械翻訳、 人手翻訳、 ビッグチームサイエンス、 翻訳精度、 心理尺度

抄録

大規模言語モデル (LLM) は心理学研究の多側面にて活用されているが,心理尺度の翻訳において人手翻訳と同等の実用性をもつかは未検証である。このManyScalesプロジェクトは,LLM翻訳の妥当性と実用性を多面的に評価し,人手翻訳との比較を行うことを目的とする。本研究は日本国内での大規模共同研究 (43名,36機関) により実施され,24種類の英語版心理尺度を対象とする。各尺度について,RパッケージLLMTranslateを用いたLLM翻訳版と,翻訳者による人手翻訳版を作成し,いずれも統一した手続きで逆翻訳を行う。両翻訳版は,(a) 専門家による意味的忠実性・自然さ・文化的妥当性の評価,(b)一般回答者による理解しやすさと自然さの評価,(c) 心理測定学的分析 (因子構造・因子得点・測定不変性・関連係数など) の観点から比較する。さらに探索的に,埋め込み表現に基づくコサイン類似度を算出し,原版項目との意味的距離を検討する。本研究により,LLM翻訳が心理尺度翻訳にどの程度活用可能であるか,また人手翻訳との差異がどの観点に表れるかを明らかにし,尺度翻訳プロセスの可視化・標準化への貢献を目指す。

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投稿日時: 2025-12-01 14:12:21 UTC

公開日時: 2025-12-09 09:34:46 UTC
研究分野
心理学・教育学