In this paper we describe design, setup and results of the speech recognition task in the framework of the Evalita campaign for the Italian language, giving details on the released corpora and tools used for the challenge. A general discussion about approaches to large vocabulary speech recognition introduces the recognition tasks. Systems are compared for recognition accuracy on audio sequences of Italian parliament. Although only a few systems have participated to the tasks, the contest provides an overview of the state-of-the-art of speech-to-text transcription technologies; the document reports systems performance, computed as Word Error Rate (WER), showing that the current approaches provide effective results. The best system achieves a WER as low as 5.4% on the released testset. © Springer-Verlag Berlin Heidelberg 2013.
CITATION STYLE
Matassoni, M., Brugnara, F., & Gretter, R. (2013). Evalita 2011: Automatic speech recognition large vocabulary transcription. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 7689 LNAI, pp. 274–285). https://doi.org/10.1007/978-3-642-35828-9_30
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