書誌事項
- タイトル別名
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- A multimodal modeling for predicting the performance of storytelling
- セツメイ コウイ ノ シツ ノ スイテイ ニ ムケタ カイワシャ ノ マルチモーダル ジョウホウ モデリング
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抄録
<p>We present a multimodal analysis of storytelling performance in group conversation as evaluated by external observers. A new multimodal data corpus, including the performance score of participants, is collected through group storytelling task. We extract multimodal features regarding explanators and listener from a manual description of spoken dialog and from various nonverbal patterns. We also extract multimodal co-occurrence features, such as utterance of explanator overlapped with listener's back channel. In the experiment, we modeled the relationship between the performance indices and the multimodal features using machine learning techniques. Experimental results show that the highest accuracy is 82% for the total storytelling performance (sum of score of indices) obtained with a combination of verbal and nonverbal features in a binary classification task.</p>
収録刊行物
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- 人工知能学会研究会資料 言語・音声理解と対話処理研究会
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人工知能学会研究会資料 言語・音声理解と対話処理研究会 74 (0), 07-, 2015-07-22
一般社団法人 人工知能学会
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詳細情報 詳細情報について
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- CRID
- 1390570000438899712
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- NII論文ID
- 40020538423
- 130008057653
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- NII書誌ID
- AN10432166
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- ISSN
- 24364576
- 09185682
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- NDL書誌ID
- 026615460
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- 本文言語コード
- ja
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- データソース種別
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- JaLC
- NDL
- CiNii Articles
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- 抄録ライセンスフラグ
- 使用可