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We present a novel approach to improve the output of optical character recognition (OCR) systems by first detecting duplicate passages in their output and then performing consensus decoding combined with a language model. This approach is orthogonal to, and may be combined with, previously proposed methods for combining the output of different OCR systems on the same image or the output of the same...
Connectionist Temporal Classification (CTC) model has achieved state-of-the-art LVCSR performance. However, due to the introduction of the blank symbol, word-level confidence measures (CM) based on CTC model can not be easily calculated by directly using the traditional phone posterior normalization or confusion network (CN) approaches. Recently, a phone synchronous decoding (PSD) framework has been...
The design and evaluation of subword-based spoken term detection (STD) systems depends on various factors, such as language, type of the speech to be searched and application scenario. The choice of the subword unit and search approach, however, is oftentimes made regardless of these factors. Therefore, we evaluate two subword STD systems across two data sets with varying properties to investigate...
Offline handwriting recognition (OHR) is an extremely challenging task because of many factors including variations in writing style, writing device and material, and noise in the scanning and collection process. Due to the diverse nature of the above challenges, it is highly unlikely that a single recognition technique can address all the characteristics of real-world handwritten documents. Therefore,...
We consider block noncoherent detection of hexagonal quadrature amplitude modulation (QAM). We focus on hexagonal constellations generated from a Voronoi code. We find that these constellations are particularly well suited to noncoherent detection because they avoid most of the identifiability problems that occur with more traditional constellations. We describe a fast, approximate, noncoherent detection...
Recently there has been a lot of interest in confusion network re-scoring using sophisticated and complex knowledge sources. Traditionally, re-scoring has been carried out by the N-best list method or by the lattices or confusion network dynamic programming method. Although the dynamic programming method is optimal, it allows for the incorporation of only Markov knowledge sources. N-best lists, on...
Confusion network (CN), a compact representation of lattice, has been arousing more and more attention in the area of speech recognition. In the paper, a novel lattice segmentation based CN generation method is proposed for remarkably reducing time complexity. Confidence based lattice segmentation algorithm is designed to cut lattices. The experimental results on a Chinese continuous speech database...
In this paper, we present a fast re-synchronization algorithm for permutation coded sequences. The new algorithm combines the dynamic algorithm and a Viterbi-like decoding algorithm for trellis codes. The new algorithm has a polynomial time complexity O(N), where N denotes the length of the sequence. A possible application to M-ary FSK for the CENELEC A band power-line communications (PLC) is considered.
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