检索结果-内蒙古大学图书馆

IEEE International Conference on Acoustics, Speech and Signal Processing

作者： Dario Bertero Pascale Fung Human Language Technology Center Department of Electronic and Computer Engineering The Hong Kong University of Science and Technology Clear Water Bay Hong Kong

ISBN: (纸本)9781509041183

We propose a real-time Convolutional Neural Network model for speech emotion detection. Our model is trained from raw audio on a small dataset of TED talks speech data, manually annotated into three emotion classes: "Angry", "Happy" and "Sad". It achieves an average accuracy of 66.1%, 5% higher than a feature-based SVM baseline, with an evaluation time of few hundred milliseconds. We also provide an in-depth model visualization and analysis. We show how our neural network effectively activates during the speech sections of the waveform regardless of the emotion, ignoring the silence parts which do not contain information. On the frequency domain the CNN filters distribute throughout all the spectrum range, with higher concentration around the average pitch range related to that emotion. Each filter also activates at multiple frequency intervals, presumably due to the additional contribution of amplitude-related feature learning. Our work will allow faster and more accurate emotion detection modules for human-machine empathetic dialog systems and other related applications.

关键词： deep learning emotion detection convolutional neural networks neural network visualization Emotions Machine Learning Speech interactive systems FAM155B gene transferred electron devices Neural network Frequency-domain analysis

来源：评论

学校读者我要写书评

暂无评论

A Multiple Feature Approach for Disorder Normalization in Clinical Notes

引用

Wuhan University Journal of Natural sciences 2016年第6期21卷 482-490页

作者： Lü Chen CHEN Bo Lü Chaozhen QIU Likun JI Donghong School of Computer Wuhan University Department of Chinese Language and Literature Hubei University of Art and Science Shandong Key Lab of Language Resource Development and Application Ludong University

In this paper we propose a multiple feature approach for the normalization task which can map each disorder mention in the text to a unique unified medical language system（UMLS）concept unique identifier（CUI）. We develop a two-step method to acquire a list of candidate CUIs and their associated preferred names using UMLS API and to choose the closest CUI by calculating the similarity between the input disorder mention and each candidate. The similarity calculation step is formulated as a classification problem and multiple features（string features,ranking features,similarity features,and contextual features） are used to normalize the disorder mentions. The results show that the multiple feature approach improves the accuracy of the normalization task from 32.99% to 67.08% compared with the Meta Map baseline.

关键词： natural language processing disorder normalization Levenshtein distance semantic composition multiple features

来源：评论

学校读者我要写书评

暂无评论

Publisher Correction: The default network of the human brain is associated with perceived social isolation

引用

Nature communications 2021年第1期12卷 3202页

作者： R Nathan Spreng Emile Dimas Laetitia Mwilambwe-Tshilobo Alain Dagher Philipp Koellinger Gideon Nave Anthony Ong Julius M Kernbach Thomas V Wiecki Tian Ge Yue Li Avram J Holmes B T Thomas Yeo Gary R Turner Robin I M Dunbar Danilo Bzdok Laboratory of Brain and Cognition Montreal Neurological Institute Department of Neurology and Neurosurgery Faculty of Medicine McGill University Montreal QC Canada. nathan.spreng@***. Departments of Psychiatry and Psychology McGill University Montreal QC Canada. nathan.spreng@***. Douglas Mental Health University Institute Verdun QC HRH 1R3 Canada. nathan.spreng@***. McConnell Brain Imaging Centre Montreal Neurological Institute (MNI) McGill University Montreal QC Canada. nathan.spreng@***. Department of Biomedical Engineering Faculty of Medicine McGill University Montreal QC Canada. Laboratory of Brain and Cognition Montreal Neurological Institute Department of Neurology and Neurosurgery Faculty of Medicine McGill University Montreal QC Canada. McConnell Brain Imaging Centre Montreal Neurological Institute (MNI) McGill University Montreal QC Canada. School of Business and Economics Vrije Universiteit Amsterdam Amsterdam The Netherlands. Marketing Department the Wharton School University of Pennsylvania Pennsylvania PA USA. Department of Human Development Cornell University Ithaca NY USA. Division of Geriatrics and Palliative Medicine Weill Cornell Medical College New York NY USA. Department of Neurosurgery Neurosurgical Artificial Intelligence Laboratory Aachen (NAILA) RWTH Aachen University Hospital Aachen Germany. Quantopian Inc. Boston MA USA. Psychiatric and Neurodevelopmental Genetics Unit Center for Genomic Medicine Massachusetts General Hospital Boston MA 02114 USA. Department of Psychiatry Massachusetts General Hospital Harvard Medical School Boston MA 02114 USA. Athinoula A. Martinos Center for Biomedical Imaging Massachusetts General Hospital Charlestown MA 02129 USA. Stanley Center for Psychiatric Research Broad Institute of MIT and Harvard Cambridge MA 02138 USA. School of Computer Science McGill University Montreal QC Canada. Departments of Psychology and Psychiatry Yale University New Haven CA 06520 USA. Depa

来源：评论

学校读者我要写书评

暂无评论

State of the art metrics for aspect oriented programming

引用

AIP Conference Proceedings 2018年第1期1952卷

作者： Mazen Ismaeel Ghareb Gary Allen 1Computer Science Department. College of Science and Technology University of Human Development Sulaimani Iraq 2Department of Informatics School of Computing and Engineering University of Huddersfield Huddersfield England

The quality evaluation of software, e.g., defect measurement, gains significance with higher use of software applications. Metric measurements are considered as the primary indicator of imperfection prediction and software maintenance in various empirical studies of software products. However, there is no agreement on which metrics are compelling quality indicators for novel development approaches such as Aspect Oriented Programming (AOP). AOP intends to enhance programming quality, by providing new and novel constructs for the development of systems, for example, point cuts, advice and inter-type relationships. Hence, it is not evident if quality pointers for AOP can be derived from direct expansions of traditional OO measurements. Then again, investigations of AOP do regularly depend on established coupling measurements. Notwithstanding the late reception of AOP in empirical studies, coupling measurements have been adopted as useful markers of flaw inclination in this context. In this paper we will investigate the state of the art metrics for measurement of Aspect Oriented systems development.

关键词：

来源：评论

学校读者我要写书评

暂无评论

How blue can you get? Learning structural relationships for microtones via continuous stochastic transduction grammars 7

How blue can you get? Learning structural relationships for ...

引用

7th International Conference on Computational Creativity, ICCC 2016

作者： Wu, Dekai HKUST Human Language Technology Center Department of Computer Science and Engineering Hong Kong University of Science and Technology Hong Kong

ISBN: (纸本)9782746691551

We describe a new approach to probabilistic modeling of structural inter-part relationships between continuous-valued musical events such as microtones, through a novel class of continuous stochastic transduction grammars. Linguistic and grammar oriented models for music commonly approximate features like pitch using discrete symbols to represent ‘clean’ notes on scales. In many musical genres, however, contextual relationships between continuous values are essential to improvisational and accompaniment decisions—as with the ‘bent notes’ that blues rely heavily upon. In this paper, we study how stochastic transduction grammars or STGs, which have until now only been able to handle discrete symbols, can be generalized to model continuous valued features for such applications. STGs are interesting for modeling the learning of musical improvisation and accompaniment where parallel musical sequences interact hierarchically (compositionally) at many overlapping levels of granularity. Each part influences decisions made by other parts while at the same time satisfying contextual preferences across multiple dimensions;applications to flamenco and hip hop have recently been shown using discrete STGs. We propose to use a formulation of continuous STGs in which musical signals are finely represented as continuous values without crude quantization into discrete symbols, yet still retaining the ability to model probabilistic structural relations between multiple musical languages. We instantiate this approach for the specific class of stochastic inversion transduction grammars (SITGs), which has proven useful in many applications, via a polynomial time algorithm for expectation-maximization training of continuous SITGs. © 2016 Proceedings of the 7th International Conference on Computational Creativity, ICCC 2016. All rights reserved.

关键词： Stochastic systems

来源：评论

学校读者我要写书评

暂无评论

CharacTER: Translation Edit Rate on Character Level 1

CharacTER: Translation Edit Rate on Character Level

引用

1st Conference on Machine Translation, WMT 2016, held at the 54th Annual Meeting of the Association for Computational Linguistics, ACL 2016

作者： Wang, Weiyue Peter, Jan-Thorsten Rosendahl, Hendrik Ney, Hermann Human Language Technology and Pattern Recognition Computer Science Department RWTH Aachen University Aachen52056 Germany

ISBN: (纸本)9781945626104

Recently, the capability of character-level evaluation measures for machine translation output has been confirmed by several metrics. This work proposes translation edit rate on character level (CharacTER), which calculates the character level edit distance while performing the shift edit on word level. The novel metric shows high system-level correlation with human rankings, especially for morphologically rich languages. It outperforms the strong CHRF by up to 7% correlation on different metric tasks. In addition, we apply the hypothesis sentence length for normalizing the edit distance in CharacTER, which also provides significant improvements compared to using the reference sentence length. © 2016 Association for Computational Linguistics.

关键词： Computational linguistics

来源：评论

学校读者我要写书评

暂无评论

ESCAPE Echo SCraper and ClAssifier of PErsons: A novel tool to facilitate using voice-controlled devices for research

arXiv

引用

arXiv 2017年

作者： Firth, Nicholas C. Harding, Emma Sullivan, Mary Pat Crutch, Sebastian J. Alexander, Daniel C. Centre for Medical Image Computing Department of Computer Science UCL Dementia Research Centre University College London School of Human and Social Development Nipissing University

Smart devices have become common place in many homes, and these devices can be utilized to provide support for people with mental or physical deficits. Voice-controlled assistants are a class of smart device that collect a large amount of data in the home. In this work we present Echo SCraper and ClAssifier of Persons (ESCAPE), an open source software for the extraction of Amazon Echo interaction data, and speaker recognition on that data. We show that ESCAPE is able to extract data from a voice-controlled assistant and classify with accuracy who is talking, based on a small number of labeled audio data. Using ESCAPE to extract interactions recorded over 3 months in the first author's home yields a rich dataset of transcribed audio recordings. Our results demonstrate that using this software the Amazon Echo can be used to study participants in a naturalistic setting with minimal intrusion. We also discuss the potential for usage of voice-controlled devices together with ESCAPE to understand how diseases affect individuals, and how these data can be used to monitor disease processes in general. Copyright © 2017, The Authors. All rights reserved.

关键词： Tools

来源：评论

学校读者我要写书评

暂无评论

Understanding deep learning performance through an examination of test set difficulty: A psychometric case study

arXiv

引用

arXiv 2017年

作者： Lalor, John P. Wu, Hao Munkhdalai, Tsendsuren Yu, Hong College of Information and Computer Sciences University of Massachusetts Amherst United States Department of Psychology and Human Development Vanderbilt University Microsoft Research MontréalQC Canada Department of Computer Science University of Massachusetts Lowell United States

Interpreting the performance of deep learning models beyond test set accuracy is challenging. Characteristics of individual data points are often not considered during evaluation, and each data point is treated equally. We examine the impact of a test set question's difficulty to determine if there is a relationship between difficulty and performance. We model difficulty using well-studied psychometric methods on human response patterns. Experiments on Natural language Inference (NLI) and Sentiment Analysis (SA) show that the likelihood of answering a question correctly is impacted by the question's difficulty. As DNNs are trained with more data, easy examples are learned more quickly than hard examples. Copyright © 2017, The Authors. All rights reserved.

关键词： Sentiment analysis

来源：评论

学校读者我要写书评

暂无评论

The JHU Machine Translation Systems for WMT 2016 1

The JHU Machine Translation Systems for WMT 2016

引用

1st Conference on Machine Translation, WMT 2016, held at the 54th Annual Meeting of the Association for Computational Linguistics, ACL 2016

作者： Ding, Shuoyang Duh, Kevin Khayrallah, Huda Koehn, Philipp Post, Matt Center for Language and Speech Processing Human Language Technology Center of Excellence Department of Computer Science Johns Hopkins University BaltimoreMD United States

ISBN: (纸本)9781945626104

This paper describes the submission of Johns Hopkins University for the shared translation task of ACL 2016 First Conference on Machine Translation (WMT 2016). We set up phrase-based, hierarchical phrase-based and syntax-based systems for all 12 language pairs of this year's evaluation campaign. Novel research directions we investigated include: neural probabilistic language models, bilingual neural network language models, morphological segmentation, and the attentionbased neural machine translation model as reranking feature. © 2016 Association for Computational Linguistics.

关键词： Neural machine translation

来源：评论

学校读者我要写书评

暂无评论

Zara the supergirl: An empathetic personality recognition system

Zara the supergirl: An empathetic personality recognition sy...

引用

2016 Conference of the North American Chapter of the Association for Computational Linguistics: human language Technologies, NAACL-HLT 2016

作者： Fung, Pascale Dey, Anik Siddique, Farhad Bin Lin, Ruixi Yang, Yang Yan, Wan Yin, Ricky Chan Ho Human Language Technology Center Department of Electronic and Computer Engineering Hong Kong University of Science and Technology Hong Kong

Zara the Supergirl is an interactive system that, while having a conversation with a user, uses its built in sentiment analysis, emotion recognition, facial and speech recognition modules, to exhibit the human-like response of sharing emotions. In addition, at the end of a 5-10 minute conversation with the user, it can give a comprehensive personality analysis based on the user's interaction with Zara. This is a first prototype that has incorporated a full empathy module, the recognition and response of human emotions, into a spoken language interactive system that enhances human-robot understanding. Zara was shown at the World Economic Forum in Dalian in September 2015. © NAACL-HLT 2016 - 2016 Conference of the North American Chapter of the Association for Computational Linguistics: human language Technologies, Proceedings of the Demonstrations Session. All rights reserved.

关键词： Emotion Recognition

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：