Fully automated approach to broadcast news transcription in Czech language

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Abstract

In the paper1 we propose a complete scheme for automatic transcription of Czech TV news. The scheme first removes the music and noisy parts, then makes segmentation of the speech signal into speaker turns and consequently tries to decode and transcribe single utterances. We employ our own recognizer recently operating with a 200K-word lexicon and with a bigram language model. The overall recognition rate achieved on all the test data was 71.53%, that obtained on the read parts was 82.72%. The most serious recognition errors occur mainly in the segments that contain background music or extremely loud noise. © Springer-Verlag Berlin Heidelberg 2004.

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APA

Nouza, J., Žd’Ánský, J., & David, P. (2004). Fully automated approach to broadcast news transcription in Czech language. In Lecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science) (Vol. 3206, pp. 401–408). Springer Verlag. https://doi.org/10.1007/978-3-540-30120-2_51

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