Summary of the paper

Title Euronews: a Multilingual Speech Corpus for ASR
Authors Roberto Gretter
Abstract In this paper we present a multilingual speech corpus, designed for Automatic Speech Recognition (ASR) purposes. Data come from the portal Euronews and were acquired both from the Web and from TV. The corpus includes data in 10 languages (Arabic, English, French, German, Italian, Polish, Portuguese, Russian, Spanish and Turkish) and was designed both to train AMs and to evaluate ASR performance. For each language, the corpus is composed of about 100 hours of speech for training (60 for Polish) and about 4 hours, manually transcribed, for testing. Training data include the audio, some reference text, the ASR output and their alignment. We plan to make public at least part of the benchmark in view of a multilingual ASR benchmark for IWSLT 2014.
Topics Multilinguality, Corpus (Creation, Annotation, etc.)
Full paper Euronews: a Multilingual Speech Corpus for ASR
Bibtex @InProceedings{GRETTER14.695,
  author = {Roberto Gretter},
  title = {Euronews: a Multilingual Speech Corpus for ASR},
  booktitle = {Proceedings of the Ninth International Conference on Language Resources and Evaluation (LREC'14)},
  year = {2014},
  month = {may},
  date = {26-31},
  address = {Reykjavik, Iceland},
  editor = {Nicoletta Calzolari (Conference Chair) and Khalid Choukri and Thierry Declerck and Hrafn Loftsson and Bente Maegaard and Joseph Mariani and Asuncion Moreno and Jan Odijk and Stelios Piperidis},
  publisher = {European Language Resources Association (ELRA)},
  isbn = {978-2-9517408-8-4},
  language = {english}
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