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检索条件"主题词=Object oriented programming languages"

共 111 条记录，以下是61-70 订阅

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USING CROSS-DECODER PHONE COOCURRENCES IN PHONOTACTIC LANGUAGE RECOGNITION

USING CROSS-DECODER PHONE COOCURRENCES IN PHONOTACTIC LANGUA...

引用

IEEE International Conference on Acoustics, Speech, and Signal Processing

作者： Mikel Penagarikano Amparo Varona Luis Javier Rodriguez-Fuentes German Bordel GTTS Department of Electricity and Electronics University of the Basque Country Spain

ISBN: (纸本)9781424442959

Phonotactic language recognizers are based on the ability of phone decoders to produce phone sequences containing acoustic, phonetic and phonological information, which is partially dependent on the language. Input utterances are decoded and then scored by means of models for the target languages. Commonly, various decoders are applied in parallel and fused at the score level. A kind of complementarity effect is expected when fusing scores, since each decoder is assumed to extract different (and complementary) information from the input utterance. This assumption is supported by the performance improvements attained when fusing systems. However, decodings are processed in a fully uncoupled way, their time alignment (and the information that may be extracted from it) being completely lost. In this paper, a simple approach is proposed, which takes into account time alignment information, by considering cross-decoder phone coocurrences at the frame level. To evaluate the approach, a choice of open software (BUT front-end and phone decoders, SRI-LM toolkit, libSVM, FoCal) is used, and experiments are carried out on the NIST LRE2007 database. Adding phone coocurrences to the baseline phonotactic systems provides slight performance improvements, revealing the potential benefit of using cross-decoder dependencies for language modeling.

关键词： Language Recognition Phone Decoding Phone Coocurrence Telephone decoders temporal registration language recognition performance boost frame level Open Software modelling languages front-ends object oriented programming languages Language

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Reverse Engineering of Relational Database Schema to UML Model

Reverse Engineering of Relational Database Schema to UML Mod...

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IEEE UP Section Conference on Electrical Computer and Electronics (UPCON)

作者： Nida Iftekhar Misbahur Rahman Warsi Sherin Zafar Samia Khan Siddhartha Sankar Biswas Jamia Hamdard New Delhi India Aligarh Muslim University Aligarh India

ISBN: (纸本)9781728134567

For the evolution and maintenance of legacy systems, it is essential that they are reverse engineered. It is becoming important because in many Legacy systems, suitable documentation is not available which makes maintenance. The proposed approach extracts hidden information which is useful for maintaining a software. Application modeling and data modeling are essential for the development of the software and are used for designing application and database separately. Generally, in software systems application layer is the object-oriented programming language and database is the backend store. Modeling of these layers separately creates inconsistency. This paper proposes a technique to reverse engineer the database schema to UML model which will incorporate modeling of an object-oriented technology on top of purely relational database. Using this conversion of database schema to UML diagram, the gap between these layers is being bridged. It will provide the understanding of the legacy system in a better way. The database schema is converted into XMI format which can be imported in a UML modeling tool. The proposed approach converts the SQL database schema as well as more frequently used SELECT statements for the schema into UML model which is in the form of XMI. By importing the generated XMI file into MagicDraw, UML model is graphically represented.

关键词： data models object-oriented programming relational databases reverse engineering software maintenance SQL Unified Modeling Language UML Reverse engineering Legacy systems database schema Relational databases Software maintenance data models SQL object oriented programming relational database schema schema object orientation object oriented programming languages

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PREDICTION-ADAPTATION-CORRECTION RECURRENT NEURAL NETWORKS FOR LOW-RESOURCE LANGUAGE SPEECH RECOGNITION

PREDICTION-ADAPTATION-CORRECTION RECURRENT NEURAL NETWORKS F...

引用

IEEE International Conference on Acoustics, Speech and Signal Processing

作者： Yu Zhang Ekapol Chuangsuwanich James Glass Dong Yu MIT Computer Science and Artificial Intelligence Laboratory Microsoft Research

ISBN: (纸本)9781479999897

In this paper, we investigate the use of prediction-adaptation-correction recurrent neural networks (PAC-RNNs) for lowresource speech recognition. A PAC-RNN is comprised of a pair of neural networks in which a correction network uses auxiliary information given by a prediction network to help estimate the state probability. The information from the correction network is also used by the prediction network in a recurrent loop. Our model outperforms other state-of-the-art neural networks (DNNs, LSTMs) on IARPA-Babel tasks. Moreover, transfer learning from a language that is similar to the target language can help improve performance further.

关键词： DNN LSTM PAC-RNN Multilingual Neural network Speech recognition object oriented programming languages Multilingualism Transfer (Psychology) Language WWOX gene Network

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Encapsulating objects with confined types 01

Encapsulating objects with confined types

引用

ACM SIGPLAN Conference on object-oriented programming, Systems, languages, and Applications

作者： Christian Grothoff Jens Palsberg Jan Vitek Slt supgt 3lt/supgt Lab Department of Computer Sciences Purdue University

ISBN: (纸本)1581133359

object-oriented languages provide little support for encapsulating objects. Reference semantics allows objects to escape their defining scope. The pervasive aliasing that ensues remains a major source of software defects. This paper introduces Kacheck/J a tool for inferring object encapulation properties in large Java programs. Our goal is to develop practical tools to assist software engineers, thus we focus on simple and scalable techniques. Kacheck/J is able to infer confinement for Java classes. A class and its sublasses are confined if all of their instances are encapsulated in their defining package. This simple property can be used to identify accidental leaks of sensitive objects. The analysis is scalable and efficient; Kacheck/J is able t infer confinement on a corpus of 46,000 classes (115 MB) in 6 minutes

关键词： encapsulating object oriented programming languages Scalability Software engineering Confined Semantics Java Java programming language

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Multi-lingual speech recognition with low-rank multi-task deep neural networks

Multi-lingual speech recognition with low-rank multi-task de...

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IEEE International Conference on Acoustics, Speech and Signal Processing

作者： A. Mohan R. Rose Dept. of Electr. & Comput. Eng. McGill Univ. Montreal QC Canada

ISBN: (纸本)9781467369985

Multi-task learning (MTL) for deep neural network (DNN) multilingual acoustic models has been shown to be effective for learning parameters that are common or shared between multiple languages[1, 2]. In the MTL paradigm, the number of parameters in the output layer is large and scales with the number of languages used in training. This output layer becomes a computational bottleneck. For mono-lingual DNNs, low-rank matrix factorization (LRMF) of weight matrices have yielded large computational savings[3, 4]. The LRMF proposed in this work for MTL, is for the original languagespecific block matrices to "share" a common matrix, with resulting low-rank language specific block matrices. The impact of LRMF is presented in two scenarios, namely : (a) improving performance in a target language when auxiliary languages are included during multi-lingual training;and (b) cross-language transfer to an unseen language with only 1 hour of transcribed training data. A 44% parameter reduction in the final layer, manifests itself in providing a lower memory footprint and faster training times. An experimental study shows that the LRMF multi-lingual DNN provides competitive performance compared to a full-rank multi-lingual DNN in both scenarios.

关键词： Low-resource speech recognition Multi-lingual speech recognition Multitask Learning Neural Networks for speech recognition Language object oriented programming languages Speech recognition matrices partitioned matrix Neural network Functional training Acoustic models

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INVESTIGATION ON CROSS- AND MULTILINGUAL MLP FEATURES UNDER MATCHED AND MISMATCHED ACOUSTICAL CONDITIONS

INVESTIGATION ON CROSS- AND MULTILINGUAL MLP FEATURES UNDER ...

引用

IEEE International Conference on Acoustics, Speech, and Signal Processing

作者： Zoltan Tuske Joel Pinto Daniel Willett Ralf Schluter Human Language Technology and Pattern Recognition Computer Science Department RWTH Aachen University Nuance Communications Deutschland GmbH

ISBN: (纸本)9781479903573

In this paper, Multi Layer Perceptron (MLP) based multilingual bottleneck features are investigated for acoustic modeling in three languages -- German, French, and US English. We use a modified training algorithm to handle the multilingual training scenario without having to explicitly map the phonemes to a common phoneme set. Furthermore, the cross-lingual portability of bottleneck features between the three languages are also investigated. Single pass recognition experiments on large vocabulary SMS dictation task indicate that (1) multilingual bottleneck features yield significantly lower word error rates compared to standard MFCC features (2) multilingual bottleneck features are superior to monolingual bottleneck features trained for the target language with limited training data, and (3) multilingual bottleneck features are beneficial in training acoustic models in a low resource language where only mismatched training data is available - by exploiting the more matched training data from other languages.

关键词： MLP Bottleneck Multilingual Mismatched acoustical condition Traffic Bottlenecks CSRP3 gene Multilingualism object oriented programming languages Language acoustic modeling Training data Phonemes Error analysis

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Translation-Based Projection for Multilingual Coreference Resolution 12

Translation-Based Projection for Multilingual Coreference Re...

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Conference of the North American Chapter of the Association for Computational Linguistics: human language technologies

作者： Altaf Rahman Vincent Ng University of Texas at Dallas Richardson TX

ISBN: (纸本)9781937284206

To build a coreference resolver for a new language, the typical approach is to first coreference-annotate documents from this target language and then train a resolver on these annotated documents using supervised learning techniques. However, the high cost associated with manually coreference-annotating documents needed by a supervised approach makes it difficult to deploy coreference technologies across a large number of natural languages. To alleviate this corpus annotation bottleneck, we examine a translation-based projection approach to multilingual coreference resolution. Experimental results on two target languages demonstrate the promise of our approach.

关键词： object oriented programming languages Coreference Resolution resolvers Language natural languages Projection

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Morpheme- and POS-based ibm1 scores and language model scores for translation quality estimation 12

Morpheme- and POS-based ibm1 scores and language model score...

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Workshop on Statistical Machine Translation

作者： Maja Popovic German Research Center for Artificial Intelligence (DFKI) Language Technology (LT) Berlin Germany

ISBN: (纸本)9781622765928

We present a method we used for the quality estimation shared task of wmt 2012 involving IBMl and language model scores calculated on morphemes and pos tags. The IBM 1 scores calculated on morphemes and POS-4grams of the source sentence and obtained translation output are shown to be competitive with the classic evaluation metrics for ranking of translation systems. Since these scores do not require any reference translations, they can be used as features for the quality estimation task presenting a connection between the source language and the obtained target language. In addition, target language model scores of morphemes and POS tags are investigated as estimates for the obtained target language quality.

关键词： object oriented programming languages modelling languages original language reduced mass Translation systems

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Support for subtyping and code re-use in Timor 02

Support for subtyping and code re-use in Timor

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International Conference on Tools Pacific

作者： J. Leslie Keedy Gisela Menger Christian Heinlein University of Ulm 89069 Ulm Germany

ISBN: (纸本)9780909925888

Unlike most object oriented programming languages Timor, which has been designed to support component development, replaces the class construct with separate constructs for defining types and their implementations (which are not types). It also distinguishes between behaviourally conforming subtyping and the inclusion of behaviourally deviant interfaces in the definition of derived types. The separation of types and implementations simplifies a separation of subtyping and subclassing, facilitating the re-use of implementations of one type to implement other, unrelated types. A further technique allows a type to be mapped onto an unrelated type with different method names, such that the latter's implementations can also be re-used to implement the former. The paper concludes by outlining a substantial example based on the Timor Collection Library.

关键词： type Timor object oriented programming languages Subtypes

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Efficient methods to train multilingual bottleneck feature extractors for low resource keyword search

Efficient methods to train multilingual bottleneck feature e...

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IEEE International Conference on Acoustics, Speech and Signal Processing

作者： Chongjia Ni Cheung-Chi Leung Lei Wang Nancy F. Chen Bin Ma Institute for Infocomm Research (I2R) A*STAR Singapore

ISBN: (纸本)9781509041183

Training a bottleneck feature (BNF) extractor with multilingual data has been common in low resource keyword search. In a low resource application, the amount of transcribed target language data is limited while there are usually plenty of multilingual data. In this paper, we investigated two methods to train efficient multilingual BNF extractors for low resource keyword search. One method is to use the target language data to update an existing BNF extractor, and another method is to combine the target language data to train a new multilingual BNF extractor from the start. In these two methods, we proposed to use long short-term memory recurrent neural network based language identification to select utterances in the multilingual training data that are acoustically close to the target language. Experiments on Swahili in the OpenKWS15 data demonstrated the efficiency of our proposed methods. The first method facilitates rapid system development, while both methods outperform using baseline BNF extractors in terms of accuracy.

关键词： Keyword spotting multilingual data selection recurrent neural network language identification recurrent neural nets language recognition extraction device object oriented programming languages BACKUS-NAUR FORM biological nitrogen fixation Key Search Systems development Swahili TRAIN

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