Application of Information Retrieval Techniques to Single Writer Documents
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Information Retrieval (IR) aims at solving a ranking problem: given a query q and a corpus C, the documents of C should be ranked such that the documents relevant to q appear above the others. This task is generally performed by ranking the documen ...
This paper discusses the evaluation of automatic speech recognition (ASR) systems developed for practical applications, suggesting a set of criteria for application-oriented performance measures. The commonly used word error rate (WER), which poses ASR eva ...
This work shows Information Retrieval experiments performed over handwritten documents produced by a single writer. The same retrieval task has been performed over both manual (no errors) and automatic (Word Error Rate around 45%) transcriptions of 200 han ...
This work shows experiments on the retrieval of handwritten documents. The performance of the same state-of-the-art Information Retrieval system is compared when dealing with manual (no errors) and automatic (Word Error Rate around 50%) transcriptions of t ...
Error correcting codes are combinatorial objects that allow reliable recovery of information in presence of errors by cleverly augmenting the original information with a certain amount of redundancy. The availability of efficient means of error detection i ...
This work presents categorization experiments performed over noisy texts. By noisy it is meant any text obtained through an extraction process (affected by errors) from media other than digital texts (e.g. transcriptions of speech recordings extracted with ...
Assessing semantic similarity between text documents is a crucial aspect in Information Retrieval systems. In this work, we propose to use hyperlink information to derive a similarity measure that can then be applied to compare any text documents, with or ...
In this paper, we investigate the possibility of enhancing state-of-the-art HMM-based speech recognition systems using data-driven techniques, where whole set of training utterances is used as reference models and recognition is then performed through the ...
In this paper, we investigate the possibility of enhancing state-of-the-art HMM-based speech recognition systems using data-driven techniques, where whole set of training utterances is used as reference models and recognition is then performed through the ...
Assessing semantic similarity between text documents is a crucial aspect in Information Retrieval systems. In this paper, we propose a technique to derive a similarity measure from hyper-link information. As linked documents are generally semantically clos ...
