Hiroaki Nanjo


2022

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Image Description Dataset for Language Learners
Kento Tanaka | Taichi Nishimura | Hiroaki Nanjo | Keisuke Shirai | Hirotaka Kameko | Masatake Dantsuji
Proceedings of the Thirteenth Language Resources and Evaluation Conference

We focus on image description and a corresponding assessment system for language learners. To achieve automatic assessment of image description, we construct a novel dataset, the Language Learner Image Description (LLID) dataset, which consists of images, their descriptions, and assessment annotations. Then, we propose a novel task of automatic error correction for image description, and we develop a baseline model that encodes multimodal information from a learner sentence with an image and accurately decodes a corrected sentence. Our experimental results show that the developed model can revise errors that cannot be revised without an image.

2018

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Development of Perceptual Training Software for Realizing High Variability Training Paradigm and Self Adaptive Training Paradigm
Ruining Yang | Hiroaki Nanjo | Masatake Dantsuji
Proceedings of the 32nd Pacific Asia Conference on Language, Information and Computation

2014

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A Listenability Measuring Method for an Adaptive Computer-assisted Language Learningand Teaching System
Katsunori Kotani | Shota Ueda | Takehiko Yoshimi | Hiroaki Nanjo
Proceedings of the 28th Pacific Asia Conference on Language, Information and Computing

2011

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Compiling Learner Corpus Data of Linguistic Output and Language Processing in Speaking, Listening, Writing, and Reading
Katsunori Kotani | Takehiko Yoshimi | Hiroaki Nanjo | Hitoshi Isahara
Proceedings of 5th International Joint Conference on Natural Language Processing

2008

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Test Collections for Spoken Document Retrieval from Lecture Audio Data
Tomoyosi Akiba | Kiyoaki Aikawa | Yoshiaki Itoh | Tatsuya Kawahara | Hiroaki Nanjo | Hiromitsu Nishizaki | Norihito Yasuda | Yoichi Yamashita | Katunobu Itou
Proceedings of the Sixth International Conference on Language Resources and Evaluation (LREC'08)

The Spoken Document Processing Working Group, which is part of the special interest group of spoken language processing of the Information Processing Society of Japan, is developing a test collection for evaluation of spoken document retrieval systems. A prototype of the test collection consists of a set of textual queries, relevant segment lists, and transcriptions by an automatic speech recognition system, allowing retrieval from the Corpus of Spontaneous Japanese (CSJ). From about 100 initial queries, application of the criteria that a query should have more than five relevant segments that consist of about one minute speech segments yielded 39 queries. Targeting the test collection, an ad hoc retrieval experiment was also conducted to assess the baseline retrieval performance by applying a standard method for spoken document retrieval.

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Automatic Estimation of Word Significance oriented for Speech-based Information Retrieval
Takashi Shichiri | Hiroaki Nanjo | Takehiko Yoshimi
Proceedings of the Third International Joint Conference on Natural Language Processing: Volume-I