bert-ner-japanese
jurabi抽出される固有表現のタイプは、以下の8種類です。 - 人名 - 法人名(法人または法人に類する組織) - 政治的組織名(政治的組織名、政党名、政府組織名、行政組織名、軍隊名、国際組織名) - その他の組織名 (競技組織名、公演組織名、その他) - 地名 - 施設名 - 製品名(商品名、番組名、映画名、書籍名、歌名、ブランド名等) - イベント名
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抽出される固有表現のタイプは、以下の8種類です。 - 人名 - 法人名(法人または法人に類する組織) - 政治的組織名(政治的組織名、政党名、政府組織名、行政組織名、軍隊名、国際組織名) - その他の組織名 (競技組織名、公演組織名、その他) - 地名 - 施設名 - 製品名(商品名、番組名、映画名、書籍名、歌名、ブランド名等) - イベント名
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Mohan Xu * , Kai Li * , Guo Chen, Xiaolin Hu Tsinghua University, Beijing, China * Equal contribution 📜 ICLR 2025 | 🎶 Demo | 🤗 Dataset > TIGER is a lightweight model for speech separation which effectively extracts key acoustic features through frequency band-split, multi-scale and full-frequency-frame modeling. - **[2025-01-23]** We release the code and pre-trained model of TIGER! 🚀 - **[2025-01-23]** We release the TIGER model and the EchoSet dataset! 🚀
TIGER: Time-frequency Interleaved Gain Extraction and Reconstruction for Efficient Speech Separation Mohan Xu * , Kai Li * , Guo Chen, Xiaolin Hu Tsinghua University, Beijing, China * Equal contribution 📜 ICLR 2025 | 🎶 Demo | 🤗 Dataset > TIGER is a lightweight model for speech separation which effectively extracts key acoustic features through frequency band-split, multi-scale and full-frequency-frame modeling.
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**Hayai OCR** is an ultra-lightweight (~150M parameter) vision-to-text model engineered for ultra-fast, crop-level transcription across **Japanese, Chinese, Korean, and English**. Hayai couples **Google's SigLIP2 NaFlex** vision encoder with a **custom 12-layer causal transformer decoder**. It transcribes dense, stylized, horizontal, and vertical text in a single forward pass without requiring an intermediate text-line detection stage (e.g., DBNet/YOLO). > **Note:** Hayai is designed specifically for **crop-level recognition**. For full-page scanning, pair it with a text detector.
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