Transcription of Connectionist Temporal Classification: Labelling ...
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Connectionist Temporal Classification: Labelling ...
Connectionist Temporal Classification: Labelling UnsegmentedSequence Data with Recurrent Neural NetworksAlex Fern urgen Dalle Molle di Studi sull Intelligenza Artificiale (IDSIA), Galleria 2, 6928 Manno-Lugano, Switzerland2 Technische Universit at M unchen (TUM), Boltzmannstr. 3, 85748 Garching, Munich, GermanyAbstractMany real-world sequence learning tasks re-quire the prediction of sequences of labelsfrom noisy, unsegmented input data. Inspeech recognition, for example, an acousticsignal is transcribed into words or sub-wordunits.
provides a powerful, general mechanism for modelling time series. In addition, they tend to be robust to temporal and spatial noise. So far, however, it has not been possible to apply RNNs directly to sequence labelling. The problem is that the standard neural network objective functions are defined separately for each point in the training se-
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