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コーパスとは？ 使い方をわかりやすく解説 無料英語学習最ツール coca corpus・SKELLも紹介 - ポリグロットライフ | 言語まなび∞ラボ
はじめに コーパスとは？今回は英語学習無料ツールであるコーパスの使い方をわかりやすく解説します。コーパスとは膨大の言語データベースで言語学の研究のために使用されています。まず始めに、コーパスの意味や活用方法、無料で利用できるcoca corpusを紹介します。英語学習への効果やコロケーションについても解説します。実際にSKELLというサービスを使って、頻出動詞のコロケーションも完全整理したので、ぜひチェックしてみてください。コーパスを活用すれば、頻出の動詞やコロケーションを知ることができます。英語話者が実際に使用している語句を網羅すれば、効率よく英語学習を進めることができます。 ↓↓こちらの動画でも解説してます www.youtube.com 英単語の覚え方はこちら↓↓ www.sunafuki.com 英語脳についてはこちらで解説↓↓ www.sunafuki.com 主な参考文献 「英
GitHub - megagonlabs/jrte-corpus: Japanese Realistic Textual Entailment Corpus (NLP 2020, LREC 2020)
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GitHub - tsuruoka-lab/BSD: The Business Scene Dialogue corpus
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GitHub - 1never/open2ch-dialogue-corpus: おーぷん2ちゃんねるをクロールして作成した対話コーパス
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GitHub - stanford-oval/WikiChat: WikiChat is an improved RAG. It stops the hallucination of large language models by retrieving data from a corpus.
Large language model (LLM) chatbots like ChatGPT and GPT-4 get things wrong a lot, especially if the information you are looking for is recent ("Tell me about the 2024 Super Bowl.") or about less popular topics ("What are some good movies to watch from [insert your favorite foreign director]?"). WikiChat uses Wikipedia and the following 7-stage pipeline to makes sure its responses are factual. Eac
Click here. [ver.1.1, Google Drive link, zip, 0.26 GB] sample: ”ところが、エリュシクトーンは、ニュムペーの制止も聞かずに、デーメーテールの樫を切り倒した" (singing_voice) (speaking_voice) Third party's data: A relabel of the PJS singing corpus manually labeled by a human. https://github.com/UtaUtaUtau/pjs-manual-labels This corpus consists of speaking and singing voices. The specification is as follows. 100 short reading utterances (Voice Ac
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Building a Large Japanese Web Corpus for Large Language Models
TL;DR: This study builds a large Japanese web corpus from the Common Crawl archive, and demonstrated its effectiveness by continual pre-training on Llama 2 7B, 13B, 70B, Mistral 7B v0.1, and Mixtral 8x7B. Abstract: Open Japanese large language models (LLMs) have been trained on the Japanese portions of corpora such as CC-100, mC4, and OSCAR. However, these corpora were not created for the quality
エンジニアコラム 広い技術領域をカバーする当社の機械学習エンジニアが、 アカデミア発のAI＆機械学習技術を 紹介＆解説いたします。 − 新日英対訳コーパス − 2021.11.9 Laboro.AI Inc. Machine Learning Engineer Zhao Xinyi （※このコラムでは、当社が開発した機械翻訳モデルによる日本語訳を各セクションに掲載しています。翻訳文は、その性能を実感いただくことを目的に、いくつかの用語を置き換える以外は人手による修正は行なっておりません。そのため、一部文章に不自然な箇所も含みますことをご了承ください。） INTRODUCTION Parallel corpus is essential to Natural Language Processing (NLP) research, especially when it comes to tra
Open Japanese large language models (LLMs) have been trained on the Japanese portions of corpora such as CC-100, mC4, and OSCAR. However, these corpora were not created for the quality of Japanese texts. This study builds a large Japanese web corpus by extracting and refining text from the Common Crawl archive (21 snapshots of approximately 63.4 billion pages crawled between 2020 and 2023). This c
GitHub - megagonlabs/asdc: Accommodation Search Dialog Corpus (宿泊施設探索対話コーパス)
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Japanese Wiki Corpus
© A. C. Yu — Generated from the Japanese-English Bilingual Corpus of Wikipedia's Kyoto Articles which is translated by the National Institute of Information and Communications Technology (NICT) from Japanese sentences on Wikipedia, used under CC BY-SA.
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Shinnosuke Takamichi (高道 慎之介) - pjs_corpus
GitHub - mmorise/ita-corpus: ITAコーパスの文章リスト
A New Japanese-English Parallel Corpus – 株式会社Laboro.AI
Building a Large Japanese Web Corpus for Large Language Models
mhikky.seesaa.net
user.keio.ac.jp/~rhotta
cururin.com
www.nhk.or.jp
note.com/nemuhon
www.afpbb.com