Dear all,

we are happy to announce that there will be a special issue of MT Journal on 
the topic of Spoken Language Translation.

Submissions will be due by July 15th. Please find the full CfP below.

We are looking forward to receiving your submissions.


*********** CFP: Machine Translation Journal *************

**** Special Issue on Spoken Language Translation ****

Guest editors: 

Alex Waibel (Carnegie Mellon University / Karlsruhe Institute of Technology)

Sebastian Stüker (Karlsruhe Institute of Technology)

Marcello Federico (Fondazione Bruno Kessler)

Satoshi Nakamura (Nara Institute of Science and Technology)

Hermann Ney (RWTH Aachen University)

Dekai Wu (The Hong Kong University of Science and Technology)


Spoken language translation (SLT) is the science of automatic translation of 
spoken language.  It may be tempting to view spoken language as nothing more 
than language (as in text) with an added spoken verbalization preceding it.  
Translation of speech could then be achieved by simply applying automatic 
speech recognition (ASR or “speech-to-text”) before applying traditional 
machine translation (MT).

Unfortunately, such an overly simplistic approach does not address the 
complexities of the problem.  Not only do speech recognition errors compound 
with errors in machine translation, but spoken language also differs 
considerably in form, structure and style, so as to render the combination of 
two text-based components as ineffective.  Moreover, automatic spoken language 
translation systems serve different practical goals than voice interfaces or 
text translators, so that integrated systems and their interfaces have to be 
designed carefully and appropriately (mobile, low-latency, audio-visual, 
online/offline, interactive, etc.) around their intended deployment.

Unlike written texts, human speech is not segmented into sentences, does not 
contain punctuation, is frequently ungrammatical, contains many disfluencies, 
or sentence fragments.  Conversely, spoken language contains information about 
the speaker, gender, emotion, emphasis, social form and relationships and –in 
the case of dialog- there is discourse structure, turn-taking, back-channeling 
across languages to be considered.

SLT systems, therefore, need to consider a host of additional concerns related 
to integrated recognition and translation performance, use of social form and 
function, prosody, suitability and (depending on deployment) effectiveness of 
human interfaces, and task performance under various speed, latency, context 
and language resource constraints.

Due to continuing improvements in underlying spoken language ASR and MT 
components as well as in the integrated system designs, spoken language systems 
have become increasingly sophisticated and can handle increasingly complex 
sentences, more natural environments, discourse and conversational styles, 
leading to a variety of successful practical deployments.

In the light of 25 years of successful research and transition into practice, 
the MT Journal dedicates a special issue to the problem of Spoken Language 
Translation.  We invite submissions of papers that address issues and problems 
pertaining to the development, design and deployment of spoken language 
translation systems.  Papers on component technologies and methodology as well 
as on system designs and deployments of spoken language systems are both 


Submission guidelines:

- Authors should follow the "Instructions for Authors" available on the MT 
Journal website:

- Submissions must be limited to 25 pages (including references)

- Papers should be submitted online directly on the MT journal's submission 
website:, indicating this 
special issue in ‘article type’

Important dates:

- Paper submission: July 15th 2016.

- Notification to authors: August 3rd 2016.

- Camera-ready*: November 19th 2016.

* tentative - depending on the number of review rounds required


Karlsruhe Institute of Technology
Institute for Anthropomatics
Research Group 3-01 'Multilingual Speech Recognition'

Dr.-Ing. Sebastian Stüker
research group leader

Adenauerring 2, Building 50.20, Room 231
76131 Karlsruhe
Phone: +49 721 608 46284        
Fax: +49 721 607 721

KIT – University of the State of Baden-Wuerttemberg and National Research 
Center of the Helmholtz Association


Karlsruher Institut für Technologie (KIT)
Institut für Anthropomatik
Nachwuchsgruppe 3-01 "Multilinguale Spracherkennung"

Dr.-Ing. Sebastian Stüker

Adenauerring 2, Gebäude 50.20, Raum 231
76131 Karlsruhe
Telephon: +49 721 608 46284
Fax: +49 721 607 721

KIT – Universität des Landes Baden-Württemberg und nationales 
Großforschungszentrum in der Helmholtz-Gemeinschaft

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