“Do you really think so?” cried Elizabeth, brightening up ... “You are uniformly charming!” cried he, with an air of awkward … “I see your design, Bingley,” said his friend. … Texts in Novels Character List
Speaker Attribution Poole was asleep, and Bowman was reading on the control deck, when Hal announced: “Er—Dave, I have a report for you.” “What’s up?” “We have another bad AE-35 unit. My fault predictor indicates failure within twenty-four hours.”
Bowman was reading on the control deck, when Hal announced: “Er—Dave, I have a report for you.” “What’s up?” “We have another bad AE-35 unit. My fault predictor indicates failure within twenty-four hours.” Mention Extraction Entity Linking Speaker Attribution
on the control deck, when Hal announced: “Er—Dave, I have a report for you.” “What’s up?” “We have another bad AE-35 unit. My fault predictor indicates failure within twenty-four hours.” Direct Speech Identification Mention Extraction Entity Linking Speaker Attribution
on the control deck, when Hal announced: “Er—Dave, I have a report for you.” “What’s up?” “We have another bad AE-35 unit. My fault predictor indicates failure within twenty-four hours.” BOWMAN POOLE BOWMAN HAL Direct Speech Identification Entity Linking Speaker Attribution Mention Extraction
on the control deck, when Hal announced: “Er—Dave, I have a report for you.” “What’s up?” “We have another bad AE-35 unit. My fault predictor indicates failure within twenty-four hours.” BOWMAN POOLE BOWMAN HAL Direct Speech Identification Speaker Attribution Entity Linking Mention Extraction
really think so?” cried Elizabeth, ... Utterance by Elizabeth Verb Speaker “My dear Mr. Bennet,…” “Is that his … ” Vocative “Aye, so it …” … “Then, my …” … “Is that a …” by speaker A by speaker B by speaker A by Mr. Bennet ⚫Vocative Detection ⚫Conversational Pattern [1] Muzny et al. A Two-stage Sieve Approach for Quote Attribution, 2017, EACL [2] He et al. Identification of Speakers in Novels, 2013, ACL
12 小説全体から人物名を抽出⇛クラスタリングで作成 1パラグラフ全体をBERT/GRUの入力に使用 2. 発話文/地の文の中身を見ていない - 前後の文脈も無視 異なる年代/文体の18小説について評価 [3] Cuesta-Lazaro et al. What does the sea say to the shore? A BERT based DST style approach for speaker to dialogue attribution in novels, 2022, ACL
et al.小説会話文への話者情報付与, 2022, 国⽴国語研究所「日常会話コーパス」プロジェクト報告書 5 [4] Du et al.小説からの自由対話コーパスの自動構築, 2019, 言語処理学会第25会年次大会 [5] Miyazaki et al.発話テキストへのキャラクタ性付与のための音変化表現の分類, 2019, 自然言語処理 [6] Ishikawa et al.口調ベクトルを用いた小説発話の話者推定, 2022, 自然言語処理研究発表会 [7] Zenimoto et al. Speaker Identification of Quotes in Japanese Novels based on Gender Classification Model by BERT, 2022, PACLIC
(It is my turn) 俺は家に戻るぜ ore wa ie ni modoru ze (I am going home) 私の番だね watashi no ban da ne (It is my turn) 私は家に戻るわ watashi wa ie ni modoru wa (I am going home) 俺はこの町が好きだぜ ore wa kono machi ga suki da ze (I love this town) 発話者分類に有用 [7] Zenimoto et al. Speaker Identification of Quotes in Japanese Novels based on Gender Classification Model by BERT, 2022, PACLIC
(It is my turn) 俺は家に戻るぜ ore wa ie ni modoru ze (I am going home) 私の番だね watashi no ban da ne (It is my turn) 私は家に戻るわ watashi wa ie ni modoru wa (I am going home) 一人称と性別的な表現は共起しやすい [7] Zenimoto et al. Speaker Identification of Quotes in Japanese Novels based on Gender Classification Model by BERT, 2022, PACLIC
novelist) 83,571 男性発話文 (“俺”を含む文) 118,997 女性発話文 (“私”を含む文) [7] Zenimoto et al. Speaker Identification of Quotes in Japanese Novels based on Gender Classification Model by BERT, 2022, PACLIC
➢キュロス (男性) : 1,030 発話文 ➢その他 : 1,785 発話文 発話文例 例文 発話者(性別) ……キュロス様は、今、どちらに……? マリー(female) おはよう、マリー。 キュロス(male) 分類対象 * https://ncode.syosetu.com/n1860fv/ [7] Zenimoto et al. Speaker Identification of Quotes in Japanese Novels based on Gender Classification Model by BERT, 2022, PACLIC
da na (It is my turn) 96.5% 3.5% 88.4%の分類精度 [7] Zenimoto et al. Speaker Identification of Quotes in Japanese Novels based on Gender Classification Model by BERT, 2022, PACLIC
on the control deck, when Hal announced: “Er—Dave, I have a report for you.” “What’s up?” “We have another bad AE-35 unit. My fault predictor indicates failure within twenty-four hours.” BOWMAN POOLE BOWMAN HAL Direct Speech Identification Speaker Attribution Entity Linking Mention Extraction