scholarly journals A Multilingual and Multidomain Study on Dialog Act Recognition Using Character-Level Tokenization

Information ◽  
2019 ◽  
Vol 10 (3) ◽  
pp. 94 ◽  
Author(s):  
Eugénio Ribeiro ◽  
Ricardo Ribeiro ◽  
David de Matos
Keyword(s):  
State Of The Art ◽  
Morphological Characteristics ◽  
The State ◽  
Complementary Information ◽  
Dialog Systems ◽  
Word Level ◽  
Morphological Aspects ◽  
Multiple Domains ◽  
Domain Independent ◽  
Multiple Character

Automatic dialog act recognition is an important step for dialog systems since it reveals the intention behind the words uttered by its conversational partners. Although most approaches on the task use word-level tokenization, there is information at the sub-word level that is related to the function of the words and, consequently, their intention. Thus, in this study, we explored the use of character-level tokenization to capture that information. We explored the use of multiple character windows of different sizes to capture morphological aspects, such as affixes and lemmas, as well as inter-word information. Furthermore, we assessed the importance of punctuation and capitalization for the task. To broaden the conclusions of our study, we performed experiments on dialogs in three languages—English, Spanish, and German—which have different morphological characteristics. Furthermore, the dialogs cover multiple domains and are annotated with both domain-dependent and domain-independent dialog act labels. The achieved results not only show that the character-level approach leads to similar or better performance than the state-of-the-art word-level approaches on the task, but also that both approaches are able to capture complementary information. Thus, the best results are achieved by combining tokenization at both levels.

scholarly journals Morphological aspects of fruits, seeds, and seedlings, and anatomy of seedlings of apuleia molaris spruce ex benth

2016 ◽  
Vol 38 (2) ◽  
pp. 118-128 ◽  
Author(s):  
Alisson Rodrigo Souza Reis ◽  
Alessandra Doce Dias de Freitas ◽  
Noemi Vianna Martins Leão ◽  
Benedito Gomes dos Santos Filho
Keyword(s):  
Vascular Bundle ◽  
Scientific Knowledge ◽  
Morphological Characteristics ◽  
Plant Anatomy ◽  
The State ◽  
Fast Growing ◽  
Morphological Aspects ◽  
Field Identification ◽  
Length Width ◽  
The Common

Abstract: Apuleia molaris spruce ex benth, commonly known in Brazil as "amarelão," is a fast-growing forest plant with a potential for use in reforestation; however, there is little information about the physiology and morphology of its fruits, seeds, and seedlings. Thus, the objective of this work was to describe the morphology of the fruits, seeds, and seedlings, in addition to the anatomic patterns of seedlings, as a contribution to the technical-scientific knowledge and production of amazonian species for reforestation in the state of Pará. For this purpose, the morphological descriptions followed the parameters from specialized literature and the common techniques used in plant anatomy. The species presents leguminous fruit; seeds with pleurogram, average dimensions of 51.21, 21.33, and 2.09 mm length, width, and thickness, respectively; and seedlings with eophyll and pinnate metaphylls, cordiform, phanerocotylar germination, epigaeous, and foliaceous. Eophylls and metaphylls present uniseriate epidermis, collateral and dorsiventral vascular bundle. The morphological characteristics may help in field identification and in the identification of young plants, aiding the production of seedlings of this species. Furthermore, anatomically, the hypocotyl has no striking differences from the root.

The Technique of Raman Spectroscopy: A State-of-the-Art Comparison to Infrared

1971 ◽  
Vol 25 (4) ◽  
pp. 430-439 ◽  
Author(s):  
Howard J. Sloane
Keyword(s):  
Raman Spectroscopy ◽  
State Of The Art ◽  
The State ◽  
Point Of View ◽  
Complementary Information ◽  
Future Outlook ◽  
Sample Handling ◽  
Advantages And Disadvantages ◽  
Sampling Procedures ◽  
Made In

This paper in a tabulated summary format discusses the state-of-the-art of Raman spectroscopy for commercially available instrumentation. A comparison to infrared is made in terms of (I) instrumentation, (II) sample handling, and (III) applications. Although the two techniques yield similar and often complementary information, they are quite different from the point of view of instrumentation and sampling procedures. This leads to various advantages and disadvantages or limitations for each. These are discussed as well as the future outlook.

scholarly journals Improving the state-of-the-art in Thai semantic similarity using distributional semantics and ontological information

PLoS ONE ◽  
2021 ◽  
Vol 16 (2) ◽  
pp. e0246751
Author(s):  
Ponrudee Netisopakul ◽  
Gerhard Wohlgenannt ◽  
Aleksei Pulich ◽  
Zar Zar Hlaing
Keyword(s):  
Semantic Similarity ◽  
Language Processing ◽  
English Language ◽  
State Of The Art ◽  
Word Sense Disambiguation ◽  
Similarity Score ◽  
The State ◽  
Word Sense ◽  
Word Level ◽  
High Fraction

Research into semantic similarity has a long history in lexical semantics, and it has applications in many natural language processing (NLP) tasks like word sense disambiguation or machine translation. The task of calculating semantic similarity is usually presented in the form of datasets which contain word pairs and a human-assigned similarity score. Algorithms are then evaluated by their ability to approximate the gold standard similarity scores. Many such datasets, with different characteristics, have been created for English language. Recently, four of those were transformed to Thai language versions, namely WordSim-353, SimLex-999, SemEval-2017-500, and R&G-65. Given those four datasets, in this work we aim to improve the previous baseline evaluations for Thai semantic similarity and solve challenges of unsegmented Asian languages (particularly the high fraction of out-of-vocabulary (OOV) dataset terms). To this end we apply and integrate different strategies to compute similarity, including traditional word-level embeddings, subword-unit embeddings, and ontological or hybrid sources like WordNet and ConceptNet. With our best model, which combines self-trained fastText subword embeddings with ConceptNet Numberbatch, we managed to raise the state-of-the-art, measured with the harmonic mean of Pearson on Spearman ρ, by a large margin from 0.356 to 0.688 for TH-WordSim-353, from 0.286 to 0.769 for TH-SemEval-500, from 0.397 to 0.717 for TH-SimLex-999, and from 0.505 to 0.901 for TWS-65.

scholarly journals On Guiding Search in HTN Planning with Classical Planning Heuristics

2019 ◽  
Author(s):  
Daniel Höller ◽  
Pascal Bercher ◽  
Gregor Behnke ◽  
Susanne Biundo
Keyword(s):  
Heuristic Search ◽  
State Of The Art ◽  
The State ◽  
Hierarchical Planning ◽  
Htn Planning ◽  
Domain Independent

Planning is the task of finding a sequence of actions that achieves the goal(s) of an agent. It is solved based on a model describing the environment and how to change it. There are several approaches to solve planning tasks, two of the most popular are classical planning and hierarchical planning. Solvers are often based on heuristic search, but especially regarding domain-independent heuristics, techniques in classical planning are more sophisticated. However, due to the different problem classes, it is difficult to use them in hierarchical planning. In this paper we describe how to use arbitrary classical heuristics in hierarchical planning and show that the resulting system outperforms the state of the art in hierarchical planning.

scholarly journals Dialogue State Tracking with Incremental Reasoning

2021 ◽  
Vol 9 ◽  
pp. 557-569
Author(s):  
Lizi Liao ◽  
Le Hong Long ◽  
Yunshan Ma ◽  
Wenqiang Lei ◽  
Tat-Seng Chua
Keyword(s):  
Large Scale ◽  
State Of The Art ◽  
The State ◽  
Policy Learning ◽  
Dialogue Management ◽  
Empirical Results ◽  
Art Methods ◽  
State Tracking ◽  
Incremental Reasoning ◽  
Multiple Domains

Abstract Tracking dialogue states to better interpret user goals and feed downstream policy learning is a bottleneck in dialogue management. Common practice has been to treat it as a problem of classifying dialogue content into a set of pre-defined slot-value pairs, or generating values for different slots given the dialogue history. Both have limitations on considering dependencies that occur on dialogues, and are lacking of reasoning capabilities. This paper proposes to track dialogue states gradually with reasoning over dialogue turns with the help of the back-end data. Empirical results demonstrate that our method outperforms the state-of-the-art methods in terms of joint belief accuracy for MultiWOZ 2.1, a large-scale human--human dialogue dataset across multiple domains.

scholarly journals An Efficient Language-Independent Multi-Font OCR for Arabic Script

2020 ◽  
Author(s):  
Hussein Osman ◽  
Karim Zaghw ◽  
Mostafa Hazem ◽  
Seifeldin Elsehely
Keyword(s):  
Character Recognition ◽  
Optical Character Recognition ◽  
State Of The Art ◽  
Recognition Task ◽  
Arabic Language ◽  
The State ◽  
Character Segmentation ◽  
Word Level ◽  
Digital Document ◽  
Arabic Ocr

Optical Character Recognition (OCR) is the process of extracting digitized text from images of scanned documents. While OCR systems have already matured in many languages, they still have shortcomings in cursive languages with overlapping letters such as the Arabic language. This paper proposes a complete Arabic OCR system that takes a scanned image of Arabic Naskh script as an input and generates a corresponding digital document. Our Arabic OCR system consists of the following modules: Pre-processing, Word-level Feature Extraction, Character Segmentation, Character Recognition, and Post-processing. This paper also proposes an improved font-independent character segmentation algorithm that outperforms the state-of-the-art segmentation algorithms. Lastly, the paper proposes a neural network model for the character recognition task. The system has experimented on several open Arabic corpora datasets with an average character segmentation accuracy 98.06%, character recognition accuracy 99.89%, and overall system accuracy 97.94% achieving outstanding results compared to the state-of-the-art Arabic OCR systems.

scholarly journals Unsupervised Phonocardiogram Analysis With Distribution Density Based Variational Auto-Encoders

2021 ◽  
Vol 8 ◽  
Author(s):  
Shengchen Li ◽  
Ke Tian
Keyword(s):  
Density Estimation ◽  
System Performance ◽  
Distribution Density ◽  
State Of The Art ◽  
Gaussian Model ◽  
The State ◽  
Single Domain ◽  
Latent Space ◽  
Multiple Domains ◽  
Pcg Signals

This paper proposes an unsupervised way for Phonocardiogram (PCG) analysis, which uses a revised auto encoder based on distribution density estimation in the latent space. Auto encoders especially Variational Auto-Encoders (VAEs) and its variant β−VAE are considered as one of the state-of-the-art methodologies for PCG analysis. VAE based models for PCG analysis assume that normal PCG signals can be represented by latent vectors that obey a normal Gaussian Model, which may not be necessary true in PCG analysis. This paper proposes two methods DBVAE and DBAE that are based on estimating the density of latent vectors in latent space to improve the performance of VAE based PCG analysis systems. Examining the system performance with PCG data from the a single domain and multiple domains, the proposed systems outperform the VAE based methods. The representation of normal PCG signals in the latent space is also investigated by calculating the kurtosis and skewness where DBAE introduces normal PCG representation following Gaussian-like models but DBVAE does not introduce normal PCG representation following Gaussian-like models.

scholarly journals Deeply-learned Hybrid Representations for Facial Age Estimation

2019 ◽  
Author(s):  
Zichang Tan ◽  
Yang Yang ◽  
Jun Wan ◽  
Guodong Guo ◽  
Stan Z. Li
Keyword(s):  
Age Estimation ◽  
State Of The Art ◽  
The State ◽  
Complementary Information ◽  
Benchmark Datasets ◽  
Independent Features ◽  
Age Range ◽  
Facial Age

In this paper, we propose a novel unified network named Deep Hybrid-Aligned Architecture for facial age estimation. It contains global, local and global-local branches. They are jointly optimized and thus can capture multiple types of features with complementary information. In each branch, we employ a separate loss for each sub-network to extract the independent features and use a recurrent fusion to explore correlations among those region features. Considering that the pose variations may lead to misalignment in different regions, we design an Aligned Region Pooling operation to generate aligned region features. Moreover, a new large age dataset named Web-FaceAge owning more than 120K samples is collected under diverse scenes and spanning a large age range. Experiments on five age benchmark datasets, including Web-FaceAge, Morph, FG-NET, CACD and Chalearn LAP 2015, show that the proposed method outperforms the state-of-the-art approaches significantly.

Practical Picture Processing

1974 ◽  
Vol 32 ◽  
pp. 338-339
Author(s):  
T. A. Welton
Keyword(s):  
Radiation Damage ◽  
Coherence Length ◽  
Spatial Information ◽  
State Of The Art ◽  
Coherent Radiation ◽  
The State ◽  
Energy Spread ◽  
Electron Micrograph ◽  
Picture Processing ◽  
Molecular Skeleton

Various authors have emphasized the spatial information resident in an electron micrograph taken with adequately coherent radiation. In view of the completion of at least one such instrument, this opportunity is taken to summarize the state of the art of processing such micrographs. We use the usual symbols for the aberration coefficients, and supplement these with £ and 6 for the transverse coherence length and the fractional energy spread respectively. He also assume a weak, biologically interesting sample, with principal interest lying in the molecular skeleton remaining after obvious hydrogen loss and other radiation damage has occurred.

Hypothesis-Evidence Coordination: The State of the Art

2003 ◽  
Vol 48 (6) ◽  
pp. 826-829 ◽  
Author(s):  
Eric Amsel
Keyword(s):  
State Of The Art ◽  
The State
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