Recent Advances in Machine Learning for Spoken Language Processing
--- Special Section on MLSLP 2015 ---
Submission deadline of the manuscript: Extended to February 5, 2016

The Institute of Electronics, Information and Communication Engineers (IEICE) Transactions on Information and Systems announces a forthcoming special section on "Recent Advances in Machine Learning for Spoken Language Processing" to be published in October 2016.
This special section is organized to commemorate the 1st International Workshop on Machine Learning in Spoken Language Processing (MLSLP 2015) which was held in September 2015 in Japan. This workshop features the latest technologies in the area of machine learning for spoken language processing.
To further promote the research and interchange of ideas in the community, we take this opportunity to organize a special section focusing on machine learning for spoken language processing. We warmly invite authors of MLSLP 2015 to submit an extended version of their papers to this special section. We also welcome the submission of original papers from a broader research community.

1. Scope
- DNN-based acoustic modeling
- RNN-based language modeling
- Adaptation and normalization
- Statistical signal processing
- Advanced modeling for speech synthesis
- Voice conversion
- UBM and i-vector-based speaker recognition
- Statistical dialogue modeling
- Semantics analysis
- Speech mining
- Machine translation
- Voice activity detection and acoustic event detection
- Speaker diarization

2. Submission Instructions
- The standard number of pages is 8 for a PAPER and 2 for a LETTER. The maximum number of pages for the initial submission of a LETTER is 4. The page charges are considerably higher for extra pages. Manuscripts should be prepared according to the guideline in the "Information for Authors". The latest version is available at the web site, http://www.ieice.org/eng/shiori/mokuji_iss.html.
- This special section will accept only papers by electronic submission. Prospective authors are requested to follow carefully the submission process described below.

1. Submit a manuscript and electronic source files (TeX/Word files, figures, authors' photos and biography) via the IEICE Web site https://review.ieice.org/regist/regist_baseinfo_e.aspx. Authors should choose the [Special-ED] Recent Advances in Machine Learning for Spoken Language Processing as a "Type of Issue (Section)/Category of Transactions" on the online screen.
2. At electric submission via the IEICE Web site, authors should agree "Copyright Transfer and Page Charge Agreement".
3. Submission deadline of the manuscript: Extended to February 5, 2016

4. Contact Address
Masakiyo Fujimoto
NTT communication science laboratories, NTT corporation
2-4 Hikari-dai, Seika-cho, Souraku-gun, Kyoto, 619-0237 JAPAN
TEL +81-774-93-5164
FAX +81-774-93-1945
Email: fujimoto.masakiyo@lab.ntt.co.jp

5. Editorial Committee
Guest Editor-in-Chief: Norihide KITAOKA (Tokushima Univ.)
Guest Editor: Tomoki TODA (Nagoya Univ.), Masafumi NISHIDA (Shizuoka Univ.), Masakiyo FUJIMOTO (NTT)
Guest Associate Editors: Takanobu OBA (NTT DoCoMo), Tetsuji OGAWA (Waseda Univ.), Kazunori KOMATANI (Osaka Univ.),
Takahiro SHINOZAKI (Tokyo Institute of Technology), Tetsuya TAKIGUCHI (Kobe Univ.)，
Takashi NOSE (Tohoku Univ.), Ryuichiro HIGASHINAKA (NTT)，Daichi MOCHIHASHI (ISM),
Junichi YAMAGISHI (NII)

6.Notice to the Authors
- The term for revising the manuscript after acknowledgement of conditional acceptance for this special section could be shorter than that for regular issues (60 days) because of the tight review schedule.
- Please note that if the submitted paper is accepted, all authors, including authors of invited papers, are requested to pay for the page charges covering partial cost of publications.
- At least one of the authors must be an IEICE member when the manuscript is submitted for review. Invited papers are an exception. We recommend that authors unaffiliated with IEICE apply for membership. For membership applications, please visit http://www.ieice.org/eng/member/OM-appli.html