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Call for Participation

The International Workshop on Spoken Language Translation (IWSLT) is a yearly scientific workshop, associated with an open evaluation campaign on spoken language translation, where both scientific papers and system descriptions are presented. The 16th IWSLT will take place in Hong Kong, on November 2nd and 3rd, 2019.

 

 

Important Dates

Evaluation Campaign: Scientific papers:
June: release of train and dev data September 1st: paper submissions
July 1st – September 8th: evaluation period October 7th: notification of acceptance
Sept 22nd: system description paper due October 13th: camera-ready paper due
October 7th: review feedback  
October 13th: camera-ready paper due  

 

 

Evaluation Campaign

IWSLT will feature three evaluation tasks focusing on end-to-end speech translation, multimodel models and spontaneous speech:

  • Speech translation of audiovisual content: HowTo and TED and real lectures from English to Portuguese and German
  • Clean speech translation of spontaneous, disfluent telephone conversations from Spanish to English
  • Text translation on a less resourced language pair: English to Czech

 

Training and development data for each task will be released to the participants through the workshop website at the beginning of June 2019. The evaluation period will be from July 1st to September 8th 2019.

 

Scientific papers

The IWSLT invites submissions of scientific papers to be published in the workshop proceedings and presented in dedicated technical sessions during the workshop, either in oral or poster format. The workshop welcomes high quality, original contributions covering theoretical and practical issues in the fields of automatic speech recognition and machine translation that are applied to spoken language translation. Possible topics include, but are not limited to:

 

MT and SLT approaches Multilingual ASR and TTS
End-to-End models for SLT Multimodal speech and text translation
MT and SLT evaluation Architectures for ASR, MT and SLT
Language resources for MT and SLT Adaptation for ASR, MT and SLT
Open source software for ASR, MT and SLT Post- and Pre-processing for ASR, MT and SLT
Applications of MT and SLT Efficiency in ASR, MT and SLT