Takeshi Yamada


2009

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Bayesian Unsupervised Word Segmentation with Nested Pitman-Yor Language Modeling
Daichi Mochihashi | Takeshi Yamada | Naonori Ueda
Proceedings of the Joint Conference of the 47th Annual Meeting of the ACL and the 4th International Joint Conference on Natural Language Processing of the AFNLP

2008

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Evaluation Framework for Distant-talking Speech Recognition under Reverberant Environments: newest Part of the CENSREC Series -
Takanobu Nishiura | Masato Nakayama | Yuki Denda | Norihide Kitaoka | Kazumasa Yamamoto | Takeshi Yamada | Satoru Tsuge | Chiyomi Miyajima | Masakiyo Fujimoto | Tetsuya Takiguchi | Satoshi Tamura | Shingo Kuroiwa | Kazuya Takeda | Satoshi Nakamura
Proceedings of the Sixth International Conference on Language Resources and Evaluation (LREC'08)

Recently, speech recognition performance has been drastically improved by statistical methods and huge speech databases. Now performance improvement under such realistic environments as noisy conditions is being focused on. Since October 2001, we from the working group of the Information Processing Society in Japan have been working on evaluation methodologies and frameworks for Japanese noisy speech recognition. We have released frameworks including databases and evaluation tools called CENSREC-1 (Corpus and Environment for Noisy Speech RECognition 1; formerly AURORA-2J), CENSREC-2 (in-car connected digits recognition), CENSREC-3 (in-car isolated word recognition), and CENSREC-1-C (voice activity detection under noisy conditions). In this paper, we newly introduce a collection of databases and evaluation tools named CENSREC-4, which is an evaluation framework for distant-talking speech under hands-free conditions. Distant-talking speech recognition is crucial for a hands-free speech interface. Therefore, we measured room impulse responses to investigate reverberant speech recognition. The results of evaluation experiments proved that CENSREC-4 is an effective database suitable for evaluating the new dereverberation method because the traditional dereverberation process had difficulty sufficiently improving the recognition performance. The framework was released in March 2008, and many studies are being conducted with it in Japan.

2000

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Acoustical Sound Database in Real Environments for Sound Scene Understanding and Hands-Free Speech Recognition
Satoshi Nakamura | Kazuo Hiyane | Futoshi Asano | Takanobu Nishiura | Takeshi Yamada
Proceedings of the Second International Conference on Language Resources and Evaluation (LREC’00)