Abstract: A subtitle segmentation system employs a neural network model to find good segment boundaries. The model may be trained on millions of professionally segmented subtitles, and implicitly learns from data the underlying guidelines that professionals use. For controlling different characteristics of the output subtitles, the neural model may be combined with a number of heuristic features. To find the best segmentation according to the model combination, a dedicated beam search decoder may be implemented. The segmentation system incorporates a trained neural model comprising a word embedding layer, at least two bi-directional LSTM layers, a softmax layer and program instructions for segmenting text into subtitles.

Abstract: A subtitle segmentation system employs a neural network model to find good segment boundaries. The model may be trained on millions of professionally segmented subtitles, and implicitly learns from data the underlying guidelines that professionals use. For controlling different characteristics of the output subtitles, the neural model may be combined with a number of heuristic features. To find the best segmentation according to the model combination, a dedicated beam search decoder may be implemented. The segmentation system incorporates a trained neural model comprising a word embedding layer, at least two bi-directional LSTM layers, a softmax layer and program instructions for segmenting text into subtitles.