Тіл моделі

Speech recognition systems incorporate a language model which, at each stage of the recognition task, assigns a probabil- ity of occurrence to each word in the vocabulary. A class of …...

We attemped to improve recognition accuracy by reduc- ing the inadequacies of the lexicon and language model. Specifically we address the following three problems: (1) the best size for the …...

We present the concepts of weighted language, ~ansduction and au- tomaton from algebraic automata theory as a general framework for describing and implementing decoding cascades in speech and lan- guage …...

The paper presents a language model that develops syntactic structure and uses it to extract meaningful information from the word history, thus enabling the use of long distance dependencies. The …...

The paper presents a language model that devel- ops syntactic structure and uses it to extract mean- ingful information from the word history, thus en- abling the use of long …...

This paper presents a language model and its application to sentence structure manip- ulations for various natural language ap- plications including human-computer com- munications. Building a working natural language dialog …...

We propose a novel statistical translation model to improve translation selection of collocation. In the statistical approach that has been popularly applied for translation selection, bilingual corpora are used to …...

Language model based IR system proposed in recent 5 years has introduced the language model approach in the speech recognition area into the IR community and improves the performance of …...

In this paper we describe and evaluate a Ques- tion Answering system that goes beyond an- swering factoid questions. We focus on FAQ- like questions and answers, and build our …...

This paper presents example-based machine translation (MT) based on syntactic trans- fer, which selects the best translation by us- ing models of statistical machine translation. Example-based MT sometimes generates in- …...

This paper reveals some important properties of CFSs and applications in Chinese natural language processing (NLP). We have previously proposed a method for extracting Chinese frequent strings that contain unknown …...

. Corpus-based stochastic language models have achieved significant success in speech recognition, but construction of a corpus pertaining to a specific application is a difficult task. This paper introduces a …...

. We propose a method for building a spoken-language text corpus for a spoken- language system. Conventional methods to build a new corpus include transcribing re- corded conversations, collecting text …...

. In this paper, we present a language model based on clusters obtained by applying regular expressions to the training data and, thus, discriminating several different sentence types as, e.g. …...

Theoretically, an improvement in a language model occurs as the size of the n-grams increases from 3 to 5 or higher. As the n-gram size increases, the number of parameters …...

. In an EBMT system, we will meet the word sense disambiguation problem. The disambiguation methods used at present can’t be used easily in EBMT. We propose a new method …...

This paper proposes the use of a language representation that specifies the relationship between terms of a sentence using question words. The proposed representation is tai- lored to help the …...

One style of Multi-Engine Machine Translation architecture involves choos- ing the best of a set of outputs from different systems. Choosing the best translation from an arbitrary set, even in …...

In this paper we generalise the sen- tence compression task. Rather than sim- ply shorten a sentence by deleting words or constituents, as in previous work, we rewrite it using …...

This paper investigates the idea of adapt- ing language models for phrases that have poor translation quality. We apply a se- lective adaptation criterion which uses a classifier to locate …...

A two-stage latent prosody model-language model (LPM-LM)-based approach is proposed to identify two Mandarin accent types spoken by native speakers in Mainland China and Taiwan. The frontend LPM tokenizes and …...

We develop a general method to match un- structured text reviews to a structured list of objects. For this, we propose a lan- guage model for generating reviews that incorporates …...

We describe the system developed by the team of the National University of Singa- pore for English to Spanish machine trans- lation of News Commentary text for the WMT09 Shared …...

AbstractThe availability of large collections of text have made it possible to build language models that incorporate counts of billions of n-grams. This paper proposes two new methods of efficiently …...

A variety of information extraction techniques rely on the fact that instances of the same relation are “distributionally similar,” in that they tend to appear in similar textual con- texts. …...

We present results from a range of experi- ments on article and preposition error correc- tion for non-native speakers of English. We first compare a language model and error- specific …...

. In this paper, we investigate the language model (LM) adaptation issue for Statis- tical Machine Translation (SMT). In order to overcome the weight bias on the LM obtained from …...

Impact of the level of supervision on Web-based language model domain adaptation Domain adaptation of a language model aims at re-estimating word sequence probabilities in order to better match the …...

The performance of Phrase-Based Statis- tical Machine Translation (PBSMT) sys- tems mostly depends on training data. Many papers have investigated how to cre- ate new resources in order to increase …...

Though it is generally accepted that language models do not capture all aspects of real language, no adequate measures to quantify their shortcomings have been proposed until now. We will …...

This paper develops a new statistical method of building language models (LMs) of Japanese dialects for automatic speech recognition (ASR). One possible application is to recognize a variety of utterances …...

AbstractOur everyday language reflects our psychological and cognitive state and effects the states of other individuals. In this contribution we look at the intersection between motivational state and language. We …...

AbstractAnnotation of data is a time-consuming process, but necessary for many state-of-the-art solutions to NLP tasks, including semantic role labeling (SRL). In this paper, we show that language models may …...

We present in this paper PADIC, a Parallel Arabic DIalect Corpus we built from scratch, then we conducted experiments on cross- dialect Arabic machine translation. PADIC is composed of dialects …...

AbstractThe role of language models in SMT is to promote fluent translation output, but traditional n-gram language models are unable to capture fluency phenomena between distant words, such as some …...

AbstractIn order to apply computational linguistic analyses and pass information to downstream applications, transcriptions of speech obtained via automatic speech recognition (ASR) need to be divided into smaller meaningful units, …...

This paper presents the challenges and the methodology followed in the design of a new Input Method (IME) for the Taiwanese (Hokkien) language. We first describe the context, the motivations …...

AbstractLanguage models are used in applications as diverse as speech recognition, optical character recognition and information retrieval. They are used to predict word appearance, and to weight the importance of …...

AbstractWe present a new Bayesian HMM word alignment model for statistical machine translation. The model is a mixture of an alignment model and a language model. The alignment component is …...

In this paper, we examine the impact of employing contextual, structural information from a tree-structured document set to derive a language model. Our results show that this in- formation significantly …...

AbstractThe present article reports on efforts to improve the translation accuracy of a corpus―based Machine Translation (MT) system. In order to achieve that, an error analysis performed on past translation …...

AbstractLSTM-based language models have been shown effective in Word Sense Disambiguation (WSD). In particular, the technique proposed by Yuan et al. (2016) returned state-of-the-art performance in several benchmarks, but neither …...

In this paper, we describe a novel combination of a character-level recurrent neural-network based model and a language model applied to diacritics restoration. In many cases in the past and …...

AbstractNeural Machine Translation (NMT) typically leverages monolingual data in training through backtranslation. We investigate an alternative simple method to use monolingual data for NMT training: We combine the scores of …...

AbstractA recent research line has obtained strong results on bilingual lexicon induction by aligning independently trained word embeddings in two languages and using the resulting cross-lingual embeddings to induce word …...

AbstractSince deep learning became a key player in natural language processing (NLP), many deep learning models have been showing remarkable performances in a variety of NLP tasks. Such high performance …...

AbstractFor unsegmented languages such as Japanese and Chinese, tokenization of a sentence has a significant impact on the performance of text classification. Sentences are usually segmented with words or subwords …...

AbstractLexical substitution, i.e. generation of plausible words that can replace a particular target word in a given context, is an extremely powerful technology that can be used as a backbone …...

AbstractThis paper proposes a general purpose relation extractor that uses Wikidata descriptions to represent the relation’s surface form. The results are tested on the FewRel 1.0 dataset, which provides an …...

AbstractLanguage models have emerged as a central component across NLP, and a great deal of progress depends on the ability to cheaply adapt them (e.g., through finetuning) to new domains …...

AbstractEnd-to-end neural data-to-text (D2T) generation has recently emerged as an alternative to pipeline-based architectures. However, it has faced challenges generalizing to new domains and generating semantically consistent text. In this …...

AbstractEfficient document summarization requires evaluation measures that can not only rank a set of systems based on an average score, but also highlight which individual summary is better than another. …...

AbstractThis work presents a method of word sense clustering that differentiates homonyms and merge homophones, taking Japanese as an example, where orthographical variation causes problem for language processing. It uses …...

AbstractLong Short-Term Memory recurrent neural network (LSTM) is widely used and known to capture informative long-term syntactic dependencies. However, how such information are reflected in its internal vectors for natural …...

AbstractThe uniform information density (UID) hypothesis, which posits that speakers behaving optimally tend to distribute information uniformly across a linguistic signal, has gained traction in psycholinguistics as an explanation for …...

AbstractWhile Transformer-based text classifiers pre-trained on large volumes of text have yielded significant improvements on a wide range of computational linguistics tasks, their implementations have been unsuitable for live incremental …...

AbstractSince language models are used to model a wide variety of languages, it is natural to ask whether the neural architectures used for the task have inductive biases towards modeling …...

AbstractIn this paper, we investigate how to use limited code-switching data to implement a code-switching speech recognition system. We utilize the Transformer end-to-end model to develop our code switching speech …...

AbstractIn computational psycholinguistics, various language models have been evaluated against human reading behavior (e.g., eye movement) to build human-like computational models. However, most previous efforts have focused almost exclusively on …...

AbstractWe propose PIGLeT: a model that learns physical commonsense knowledge through interaction, and then uses this knowledge to ground language. We factorize PIGLeT into a physical dynamics model, and a …...

AbstractThe Neural Machine Translation (NMT) model is essentially a joint language model conditioned on both the source sentence and partial translation. Therefore, the NMT model naturally involves the mechanism of …...

AbstractNLP is currently dominated by language models like RoBERTa which are pretrained on billions of words. But what exact knowledge or skills do Transformer LMs learn from large-scale pretraining that …...

AbstractBehavioural consistency is a critical condition for a language model (LM) to become trustworthy like humans. Despite its importance, however, there is little consensus on the definition of LM consistency, …...

AbstractCurrent language models achieve low perplexity but their resulting generations still suffer from toxic responses, repetitiveness, and contradictions. The standard language modeling setup fails to address these issues. In this …...

AbstractNeural Network (NN) architectures are used more and more to model large amounts of data, such as text data available online. Transformer-based NN architectures have shown to be very useful …...

AbstractLanguage models are often trained on text alone, without additional grounding. There is debate as to how much of natural language semantics can be inferred from such a procedure. We …...

AbstractThis paper summarizes the participation of the L3i laboratory of the University of La Rochelle in the SemEval-2022 Task 11, Multilingual Complex Named Entity Recognition (MultiCoNER). The task focuses on …...

AbstractChinese handwritten address recognition of consignment note is an important challenge of smart logistics automation. Chinese handwritten characters detection and recognition is the key technology for this application. Since the …...

AbstractAugmentation of task-oriented dialogues has followed standard methods used for plain-text such as back-translation, word-level manipulation, and paraphrasing despite its richly annotated structure. In this work, we introduce an augmentation …...

AbstractIn retrieval-based dialogue systems, a response selection model acts as a ranker to select the most appropriate response among several candidates. However, such selection models tend to rely on context-response …...

AbstractMental disorders affect millions of people worldwide and cause interference with their thinking and behavior. Through the past years, awareness created by health campaigns and other sources motivated the study …...

AbstractMultiCoNER-II is a fine-grained Named Entity Recognition (NER) task that aims to identify ambiguous and complex named entities in multiple languages, with a small amount of contextual information available. To …...

AbstractThis case study presents a Multilingual e-commerce Project, which principal aim is to create an improved system that translates product titles and descriptions, plus other content in multiple languages. The …...