Evaluation of Text and Speech Systems

Dybkjær, Laila; Hemsen, Holmer; Minker, Wolfgang

doi:10.1007/978-1-4020-5817-2

Cited by 19 publications

(3 citation statements)

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“…These more accurate classifications make it possible to compare and analyze the scope of the different formats and standards that enable LRs to be shared. According to Ide and Romary (2007), LRs can be classified as shown in Figure 1, where: primary resources include texts, spoken data and multi-modal data;…”

Section: Classifying Linguistic Resourcesmentioning

confidence: 99%

“…A LR is a body of electronic language data used to support research and applications in the area of natural language processing (NLP) (Ide and Romary, 2007). A large number of rich sources of linguistic information has been created in several categories which sometimes overlap, including: term base, lexicon, machine readable dictionary, corpora, generative grammar, knowledge collection, transcription (from phonetic features to discourse structures), part-of-speech and sense tagging, morphological analysis, syntactic analysis, annotations, named entity recognition, co-reference annotation and so on.…”

Section: Introductionmentioning

confidence: 99%

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A survey on the exchange of linguistic resources

Lezcano

Sánchez‐Alonso

Roa-Valverde

2013

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Purpose -The purpose of this paper is to provide a literature review of the principal formats and frameworks that have been used in the last 20 years to exchange linguistic resources. It aims to give special attention to the most recent approaches to publishing linguistic linked open data on the Web. Design/methodology/approach -Research papers published since 1990 on the use of various formats, standards, frameworks and methods to exchange linguistic information were divided into two main categories: those proposing specific schemas and syntaxes to suit the requirements of a given type of linguistic data (these are referred to as offline approaches), and those adopting the linked data (LD) initiative and the semantic web technologies to support the interoperability of heterogeneous linguistic resources. For each paper, the type of linguistic resource exchanged, the framework/format used, the interoperability approach taken and the related projects were identified. Findings -The information gathered in the survey reflects an increase in recent years in approaches adopting the LD initiative. This is due to the fact that the structural and syntactic issues which arise when addressing the interoperability of linguistic resources can be solved by applying semantic web technologies. What remains an open issue in the field of computational linguistics is the development of knowledge artefacts and mechanisms to support the alignment of the different aspects of linguistic resources in order to guarantee semantic and conceptual interoperability in the linked open data (LOD) cloud. Ontologies have proved to be of great use in achieving this goal.Research limitations/implications -The research presented here is by no means a comprehensive or all-inclusive survey of all existing approaches to the exchange of linguistic resources. Rather, the aim was to highlight, analyze and categorize the most significant advances in the field. Practical implications -This survey has practical implications for computational linguists and for every application requiring new developments in natural language processing. In addition, multilingual issues can be better addressed when semantic interoperability of heterogeneous linguistic resources is achieved. Originality/value -The paper provides a survey of past and present research and developments addressing the interoperability of linguistic resources, including those where the linked data initiative has been adopted.

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Section: Classifying Linguistic Resourcesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A survey on the exchange of linguistic resources

Lezcano

Sánchez‐Alonso

Roa-Valverde

2013

Program

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“…In speech communication, we often face several types of language expectation violations, such as prosodic, semantic, and syntactic errors, especially in conversation through machine output (e.g., human–computer interaction; Koponen, 2010). Questionnaire-based subjective judgments are commonly used to rate such language expectation violations as linguistic discrepancies (Dybkjær et al, 2007). For example, regarding errors in the responses of spoken dialogue systems and machine translation, human examiners in previous research judged each sentence on an error scale from 1 to 5, unlike automatic evaluation metrics, e.g., word error rate (Lippmann, 1997; Och et al, 1999; Papineni et al, 2002).…”

Section: Introductionmentioning

confidence: 99%

Electroencephalogram-Based Single-Trial Detection of Language Expectation Violations in Listening to Speech

Tanaka

Watanabe

Maki

et al. 2019

Front. Comput. Neurosci.

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We propose an approach for the detection of language expectation violations that occur in communication. We examined semantic and syntactic violations from electroencephalogram (EEG) when participants listened to spoken sentences. Previous studies have shown that such event-related potential (ERP) components as N400 and the late positivity (P600) are evoked in the auditory where semantic and syntactic anomalies occur. We used this knowledge to detect language expectation violation from single-trial EEGs by machine learning techniques. We recorded the brain activity of 18 participants while they listened to sentences that contained semantic and syntactic anomalies and identified the significant main effects of these anomalies in the ERP components. We also found that a multilayer perceptron achieved 59.5% (semantic) and 57.7% (syntactic) accuracies.

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2015

Practical Corpus Linguistics

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Evaluation of Text and Speech Systems

Cited by 19 publications

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A survey on the exchange of linguistic resources

A survey on the exchange of linguistic resources

Electroencephalogram-Based Single-Trial Detection of Language Expectation Violations in Listening to Speech

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