Natural language processing with neural networks

Outlook

The example shown here is the subject of current research in the field of language technology. Scientists are currently still investigating questions such as: Which weighing of the individual factors, such as translation quality and synchronization quality, optimizes the overall quality? At which point exactly do people even notice that the lip-sync is no longer perfect?

It is also important to remember that world languages vary considerably. Consequently, this problem is so complex that a single model cannot do justice to it. As a result, it is essential to train separate models for the different pairs of languages to be translated.

Infos

  1. "Computing Machinery and Intelligence" by A.M. Turing, Mind, volume LIX, October 1950, pp. 443-460, https://academic.oup.com/mind/article/LIX/236/433/986238
  2. Karpathy (2015); http://karpathy.github.io/2015/05/21/rnn-effectiveness/

The Author

Timo Baumann is Professor of Artificial Intelligence at the Faculty of Computer Science and Mathematics at OTH Regensburg where he focuses on natural language processing. His research focuses on socially and interactively adequate conversational agents, prosody processing, and automatic lip-synchronous dubbing. Christian Schuler is currently studying computer science in the Master of Science program at the University of Hamburg. His bachelor thesis was about the acquisition of perceived quality of lip synchronicity in audiovisually translated material.

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