IEEE/ACM TRANSACTIONS ON
AUDIO, SPEECH, AND LANGUAGE PROCESSING
A PUBLICATION OF
THE IEEE SIGNAL PROCESSING SOCIETY AND THE
ASSOCIATION FOR COMPUTING MACHINERY
Important Announcement - August 2, 2013
IEEE and ACM are pleased to announce that the IEEE Transactions on Audio, Speech, and Language Processing and the ACM Transactions on Speech and Language Processing will be published jointly as the IEEE/ACM Transactions on Audio, Speech, and Language Processing, starting January 2014. Papers from the new Transactions will appear in both IEEE Xplore and the ACM Digital Library. Publication will be managed by IEEE as a hybrid journal, allowing either traditional or open access manuscript submission. The new journal welcomes novel contributions in all areas covered by the two journals, which includes audio, speech, and language processing and the sciences that support them.
A revised and expanded version of the EDICS will be posted later this month. For new submissions, go to http://mc.manuscriptcentral.com/sps-ieee.
The IEEE/ACM Transactions on Audio, Speech, and Language Processing is dedicated to innovative theory and methods for processing signals representing audio, speech and language, and their applications. This includes analysis, synthesis, enhancement, transformation, classification and interpretation of such signals as well as the design, development, and evaluation of associated signal processing systems.
Machine learning and pattern analysis applied to any of the above areas is also welcome.
The Transactions encourages authors to make their publications reproducible by making all information needed to reproduce the presented results available online. This typically requires publishing the code and data used to produce the publication's figures and tables on a website; see the supplemental materials section of the information for authors. It gives other researchers easier access to the work, and facilitates fair comparisons.
It is now possible to submit for review and publish in Xplore supporting multimedia material such as speech samples, images, movies, matlab code etc. A multimedia graphical abstract can also be displayed along with the traditional text. More information is available under Multimedia Materials at the IEEE Author Digital Tool Box.
Impact factor: 2.475
Eigenfactor™ Score: 0.01070
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