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Research on Voiceprint Recognition of Camouflage Voice Based on Deep Belief Network

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International Journal of Automation and computing 2021年第6期18卷 947-962页

作者： Nan Jiang ting liu College of Public Security Information Technology and Intelligence Criminal Investigation Police University of ChinaShenyang 110854China College of Light Industry Liaoning UniversityShenyang 110036China

The problem of disguised voice recognition based on deep belief networks is studied. A hybrid feature extraction algorithm based on formants, Gammatone frequency cepstrum coefficients(GFCC) and their different coefficients is proposed to extract more discriminative speaker features from the original voice data. Using mixed features as the input of the model, a masquerade voice library is constructed. A masquerade voice recognition model based on a depth belief network is proposed. A dropout strategy is introduced to prevent overfitting, which effectively solves the problems of traditional Gaussian mixture models, such as insufficient modeling ability and low discrimination. Experimental results show that the proposed disguised voice recognition method can better fit the feature distribution, and significantly improve the classification effect and recognition rate.

关键词： Disguised voice recognition deep belief network feature extraction Gammatone frequency cepstrum coefficients(GFCC) dropout

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Predictability of the upper ocean heat content in a Community Earth System Model ensemble prediction system

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Acta Oceanologica Sinica 2024年第1期43卷 1-10页

作者： ting liu Wenxiu Zhong State Key Laboratory of Satellite Ocean Environment Dynamics Second Institute of OceanographyMinistry of Natural ResourcesHangzhou 310012China Southern Marine Science and Engineering Guangdong Laboratory(Zhuhai) Zhuhai 519082China School of Atmospheric Sciences Sun Yat-Sen UniversityZhuhai 519082China

Upper ocean heat content(OHC)has been widely recognized as a crucial precursor to high-impact climate variability,especially for that being indispensable to the long-term memory of the *** the predictability of OHC using state-of-the-art climate models is invaluable for improving and advancing climate *** developed retrospective forecast experiments,based on a Community Earth System Model ensemble prediction system,offer a great opportunity to comprehensively explore OHC *** results indicate that the skill of actual OHC predictions varies across different oceans and diminishes as the lead time of prediction *** spatial distribution of the actual prediction skill closely resembles the corresponding persistence skill,indicating that the persistence of OHC serves as the primary predictive signal for its *** decline in actual prediction skill is more pronounced in the Indian and Atlantic oceans than in the Pacific Ocean,particularly within tropical ***,notable seasonal variations in the actual prediction skills across different oceans align well with the phase-locking features of OHC *** potential predictability of OHC generally surpasses the actual prediction skill at all lead times,highlighting significant room for improvement in current OHC predictions,especially for the North Indian Ocean and the Atlantic *** such improvements necessitates a collaborative effort to enhance the quality of ocean observations,develop effective data assimilation methods,and reduce model bias.

关键词： ocean heat content prediction skill retrospective forecast experiment

Zero-inflated non-central negative binomial distribution

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Applied Mathematics(A Journal of Chinese Universities) 2022年第2期37卷 187-198页

作者： TIAN Wei-zhong liu ting-ting YANG Yao-ting College of Big Data and Internet Shenzhen Technology UniversityShenzhen 518118China School of Science Xi'an University of TechnologyXi'an 710054China

In this article, the zero-inflated non-central negative binomial(ZINNB) distribution is introduced. Some of its basic properties are obtained. In addition, we use the maximum likelihood estimation method to estimate t... 详细信息

关键词： zero-in ated non-central negative binomial distribution maximum likelihood estimation good-ness of fit

A survey of discourse parsing

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Frontiers of Computer Science 2022年第5期16卷 85-96页

作者： Jiaqi LI Ming liu Bing QIN ting liu School of Computer Science and Technology Harbin Institute of TechnologyHarbin 150001China Peng Cheng Laboratory Shenzhen 518052China

Discourse parsing is an important research area in natural language processing(NLP),which aims to parse the discourse structure of coherent *** this survey,we introduce several different kinds of discourse parsing tasks,mainly including RST-style discourse parsing,PDTB-style discourse parsing,and discourse parsing for multiparty *** these tasks,we introduce the classical and recent existing methods,especially neural network *** that,we describe the applications of discourse parsing for other NLP tasks,such as machine reading comprehension and sentiment ***,we discuss the future trends of the task.

关键词： discourse parsing discourse structure RST PDTB STAC

Bidirectional Transformer with absolute-position aware relative position encoding for encoding sentences

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Frontiers of Computer Science 2023年第1期17卷 63-71页

作者： Le QI Yu ZHANG ting liu School of Computer Science and Technology Harbin Institute of TechnologyHarbin 150001China

Transformers have been widely studied in many natural language processing (NLP) tasks, which can capture the dependency from the whole sentence with a high parallelizability thanks to the multi-head attention and the position-wise feed-forward network. However, the above two components of transformers are position-independent, which causes transformers to be weak in modeling sentence structures. Existing studies commonly utilized positional encoding or mask strategies for capturing the structural information of sentences. In this paper, we aim at strengthening the ability of transformers on modeling the linear structure of sentences from three aspects, containing the absolute position of tokens, the relative distance, and the direction between tokens. We propose a novel bidirectional Transformer with absolute-position aware relative position encoding (BiAR-Transformer) that combines the positional encoding and the mask strategy together. We model the relative distance between tokens along with the absolute position of tokens by a novel absolute-position aware relative position encoding. Meanwhile, we apply a bidirectional mask strategy for modeling the direction between tokens. Experimental results on the natural language inference, paraphrase identification, sentiment classification and machine translation tasks show that BiAR-Transformer achieves superior performance than other strong baselines.

关键词： Transformer relative position encoding bidirectional mask strategy sentence encoder

An electrochromic coordination nanosheet for robust CO_(2) photoreduction via ligand-based electron transfer

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Nano Research 2022年第7期15卷 5902-5911页

作者： Longxin Chen ting liu Duobin Chao School of Materials Science and Chemical Engineering Ningbo UniversityNingbo 315211China

A coordination nanosheet composed of[Fe(tpy)_(2)]^(2+)(tpy=2,2':6',2''-terpyridine)units,showing reversible electrochromism at the ligand-based cathodic potential,has been prepared through a liquid/liquid interfacial *** noble metal-free nanosheet exhibited a CO evolution rate of 114.3 mmol·g−1·h−1 with the selectivity up to 99.3%under visible light irradiation in the presence of water,which is in the front rank of heterogeneous catalysis for CO_(2) *** robust photocatalytic performance is due to efficient ligand-based electron transfer through long-livedπradical anion tpy·−with a lifetime more than 25 min,as evidenced by in situ electron paramagnetic resonance(EPR)and ultraviolet-visible-near infrared(UV-vis-NIR)spectroscopy ***(II)cation in[Fe(tpy)_(2)]^(2+)mainly contributes to enhancing reduction potentials of ligand and stabilizingπradical anion tpy·−.This ligand-based electron transfer with the aid of metal cation represents a promising strategy for selective CO_(2) photoreduction,especially towards gaining CO from CO_(2).

关键词： photocatalysis CO_(2)reduction electron transfer coordination nanosheet electrochromism

Improved smoothed L0 reconstruction algorithm for ISI sparse channel estimation

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The Journal of China Universities of Posts and Telecommunications 2014年第2期21卷 40-47页

作者： liu ting ZHOU Jie Department of Communications Nanjing University of Information Science and Technology Department of Electronic and Electrical Engineering Niigata University

In this paper, the problem of inter symbol interference （ISI） sparse channel estimation in wireless communication with the application of compressed sensing is investigated. However, smoothed L0 norm algorithm （SL0） has ＇notched effect＇ due to the negative iterative gradient direction. Moreover, the property of continuous function in SL0 is not steep enough, which results in inaccurate estimations and low convergence. Afterwards, we propose the Lagrange multipliers as well as Newton method to optimize SL0 algorithm in order to obtain a more rapid and efficient signal reconstruction algorithm, improved smoothed L0 （ISL0）. ISI channel estimation will have a direct effect on the performance of ISI equalizer at the receiver. So, we design a pre-filter model which with no considerable loss of optimality and do analyses of the equalization methods of the sparse multi-path channel. Real-time simulation results clearly show that the ISL0 algorithm can estimate the ISI sparse channel much better in both signal noise ratio （SNR） and compression levels. In the same channel conditions, ISL0 algorithm has been greatly improved when compared with the SL0 algorithm and other compressed-sensing algorithms.

关键词： compressed-sensing channel model ISI improved SLO algorithm sparse channel estimation MIMO system

Topic hierarchy construction from heterogeneous evidence

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Frontiers of Computer Science 2016年第1期10卷 136-146页

作者： Han XUE Bing QIN ting liu Shen liu School of Computer Science and Technology Harbin Institute of Technology Harbin 150001 China Harbin Engineering University Library Harbin Engineering University Harbin 150001 China

Existing studies on hierarchy construction mainly focus on text corpora and indiscriminately mix numerous top- ics, thus increasing the possibility of knowledge acquisition bottlenecks and misconceptions. To address these problems and provide a comprehensive and in-depth representation of domain specific topics, we propose a novel topic hierar- chy construction method with real-time update. This method combines heterogeneous evidence from multiple sources in- cluding folksonomy and encyclopedia, separately in both ini- tial topic hierarchy construction and topic hierarchy improve- ment. Results of comprehensive experiments indicate that the proposed method significantly outperforms state-of-the- art methods （t-test, p-value 〈 0.000 1）; recall has particularly improved by 20.4% to 38.7%.

关键词： hierarchy construction Chinese topic hierarchy,folksonomy heterogeneous evidence hierarchy update

Generating Chinese named entity data from parallel corpora

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Frontiers of Computer Science 2014年第4期8卷 629-641页

作者： Ruiji FU Bing QIN ting liu School of Computer Science and Technology Harbin Institute of Technology Harbin 150001 China

Annotating named entity recognition （NER） training corpora is a costly but necessary process for supervised NER approaches. This paper presents a general framework to generate large-scale NER training data from parallel corpora. In our method, we first employ a high performance NER system on one side of a bilingual corpus. Then, we project the named entity （NE） labels to the other side according to the word level alignments. Finally, we propose several strategies to select high-quality auto-labeled NER training data. We apply our approach to Chinese NER using an English-Chinese parallel corpus. Experimental results show that our approach can collect high-quality labeled data and can help improve Chinese NER.

关键词： named entity recognition Chinese named entity training data generating parallel corpora