This paper describes speech translation from Amharic-to-English, particularly Automatic Speech Recognition (ASR) with post-editing feature and AmharicEnglish Statistical Machine Translation (SMT). ASR experiment is conducted using morpheme language model (LM) and phoneme acoustic model (AM). Likewise, SMT conducted using word and morpheme as unit. Morpheme based translation shows a 6.29 BLEU sc...

OBJECTIVE To assess the clinical value of four models for the prediction of cardiac surgery-associated acute kidney injury (CSA-AKI) and severe AKI which renal replacement therapy was needed (RRT-AKI) in Chinese patients. METHODS 1587 patients who underwent cardiac surgery in the department of cardiac surgery in the Zhongshan Hospital, Fudan University, between January 2013 and December 2013 ...

Pitch discrimination interference (PDI) refers to an impairment in the ability to discriminate changes in the fundamental frequency (F0) of a target harmonic complex, caused by another harmonic complex (the interferer) presented simultaneously in a remote spectral region. So far, PDI has been demonstrated for target complexes filtered into a higher spectral region than the interferer and contai...

Word level confidence measures are of use in many areas of speech recognition. Comparing the hypothesized word score to the score of a ‘filler’ model has been the most popular confidence measure because it is highly efficient, and does not require a large amount of training data. This paper explores an extension of this technique which also compares the hypothesized word score to the scores of ...

Effort testing has become commonplace in clinical practice. Recent research has shown that performance on effort tests is highly correlated with performance on neuropsychological measures. Clinical application of effort testing is highly dependent on research derived interpretive guidelines. The Victoria Symptom Validity Test (VSVT) is one of many measures currently used in clinical practice. T...

In natural language processing (NLP), word sense disambiguation (WSD) is defined as the task of assigning the appropriate meaning (sense) to a given word in a text or discourse. Natural language is ambiguous, so that many words can be interpreted in multiple ways depending on the context in which they occur. The computational identification of meaning for words in context is called word sense d...

This paper describes the neural dependency parser submitted by Stanford to the CoNLL 2017 Shared Task on parsing Universal Dependencies. Our system uses relatively simple LSTM networks to produce part of speech tags and labeled dependency parses from segmented and tokenized sequences of words. In order to address the rare word problem that abounds in languages with complex morphology, we includ...

This chapter focuses on unsupervised corpus-based methods of word sense discrimination that are knowledge-lean, and do not rely on external knowledge sources such as machine readable dictionaries, concept hierarchies, or sense-tagged text. They do not assign sense tags to words; rather, they discriminate among word meanings based on information found in unannotated corpora. This chapter reviews...

This chapter focuses on unsupervised corpus-based methods of word sense discrimination that are knowledge-lean, and do not rely on external knowledge sources such as machine readable dictionaries, concept hierarchies, or sense-tagged text. They do not assign sense tags to words; rather, they discriminate among word meanings based on information found in unannotated corpora. This chapter reviews...