Normunds Gruzitis

Also published as: Normunds Grūzītis


2020

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Development and Evaluation of Speech Synthesis Corpora for Latvian
Roberts Darģis | Peteris Paikens | Normunds Gruzitis | Ilze Auzina | Agate Akmane
Proceedings of the 12th Language Resources and Evaluation Conference

Text to speech (TTS) systems are necessary for all languages to ensure accessibility and availability of digital language services. Recent advances in neural speech synthesis have eText to speech (TTS) systems are necessary for any language to ensure accessibility and availability of digital language services. Recent advances in neural speech synthesis have enabled the development of such systems with a data-driven approach that does not require significant development of language-specific tools. However, smaller languages often lack speech corpora that would be sufficient for training current neural TTS models, which require at least 30 hours of good quality audio recordings from a single speaker in a noiseless environment with matching transcriptions. Making such a corpus manually can be cost prohibitive. This paper presents an unsupervised approach to obtain a suitable corpus from unannotated recordings using automated speech recognition for transcription, as well as automated speaker segmentation and identification. The proposed method and software tools are applied and evaluated on a case study for developing a corpus suitable for Latvian speech synthesis based on Latvian public radio archive data.nabled the development of such systems with a data-driven approach that does not require much language-specific tool development. However, smaller languages often lack speech corpora that would be sufficient for training current neural TTS models, which require approximately 30 hours of good quality audio recordings from a single speaker in a noiseless environment with matching transcriptions. Making such a corpus manually can be cost prohibitive. This paper presents an unsupervised approach to obtain a suitable corpus from unannotated recordings using automated speech recognition for transcription, as well as automated speaker segmentation and identification. The proposed methods and software tools are applied and evaluated on a case study for developing a corpus suitable for Latvian speech synthesis based on Latvian public radio archive data.

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Abstract Syntax as Interlingua: Scaling Up the Grammatical Framework from Controlled Languages to Robust Pipelines
Aarne Ranta | Krasimir Angelov | Normunds Gruzitis | Prasanth Kolachina
Computational Linguistics, Volume 46, Issue 2 - June 2020

Abstract syntax is an interlingual representation used in compilers. Grammatical Framework (GF) applies the abstract syntax idea to natural languages. The development of GF started in 1998, first as a tool for controlled language implementations, where it has gained an established position in both academic and commercial projects. GF provides grammar resources for over 40 languages, enabling accurate generation and translation, as well as grammar engineering tools and components for mobile and Web applications. On the research side, the focus in the last ten years has been on scaling up GF to wide-coverage language processing. The concept of abstract syntax offers a unified view on many other approaches: Universal Dependencies, WordNets, FrameNets, Construction Grammars, and Abstract Meaning Representations. This makes it possible for GF to utilize data from the other approaches and to build robust pipelines. In return, GF can contribute to data-driven approaches by methods to transfer resources from one language to others, to augment data by rule-based generation, to check the consistency of hand-annotated corpora, and to pipe analyses into high-precision semantic back ends. This article gives an overview of the use of abstract syntax as interlingua through both established and emerging NLP applications involving GF.

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Deriving a PropBank Corpus from Parallel FrameNet and UD Corpora
Normunds Gruzitis | Roberts Darģis | Laura Rituma | Gunta Nešpore-Bērzkalne | Baiba Saulite
Proceedings of the International FrameNet Workshop 2020: Towards a Global, Multilingual FrameNet

We propose an approach for generating an accurate and consistent PropBank-annotated corpus, given a FrameNet-annotated corpus which has an underlying dependency annotation layer, namely, a parallel Universal Dependencies (UD) treebank. The PropBank annotation layer of such a multi-layer corpus can be semi-automatically derived from the existing FrameNet and UD annotation layers, by providing a mapping configuration from lexical units in [a non-English language] FrameNet to [English language] PropBank predicates, and a mapping configuration from FrameNet frame elements to PropBank semantic arguments for the given pair of a FrameNet frame and a PropBank predicate. The latter mapping generally depends on the underlying UD syntactic relations. To demonstrate our approach, we use Latvian FrameNet, annotated on top of Latvian UD Treebank, for generating Latvian PropBank in compliance with the Universal Propositions approach.

2018

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Creation of a Balanced State-of-the-Art Multilayer Corpus for NLU
Normunds Gruzitis | Lauma Pretkalnina | Baiba Saulite | Laura Rituma | Gunta Nespore-Berzkalne | Arturs Znotins | Peteris Paikens
Proceedings of the Eleventh International Conference on Language Resources and Evaluation (LREC 2018)

2017

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RIGOTRIO at SemEval-2017 Task 9: Combining Machine Learning and Grammar Engineering for AMR Parsing and Generation
Normunds Gruzitis | Didzis Gosko | Guntis Barzdins
Proceedings of the 11th International Workshop on Semantic Evaluation (SemEval-2017)

By addressing both text-to-AMR parsing and AMR-to-text generation, SemEval-2017 Task 9 established AMR as a powerful semantic interlingua. We strengthen the interlingual aspect of AMR by applying the multilingual Grammatical Framework (GF) for AMR-to-text generation. Our current rule-based GF approach completely covered only 12.3% of the test AMRs, therefore we combined it with state-of-the-art JAMR Generator to see if the combination increases or decreases the overall performance. The combined system achieved the automatic BLEU score of 18.82 and the human Trueskill score of 107.2, to be compared to the plain JAMR Generator results. As for AMR parsing, we added NER extensions to our SemEval-2016 general-domain AMR parser to handle the biomedical genre, rich in organic compound names, achieving Smatch F1=54.0%.

2016

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Tēzaurs.lv: the Largest Open Lexical Database for Latvian
Andrejs Spektors | Ilze Auzina | Roberts Dargis | Normunds Gruzitis | Peteris Paikens | Lauma Pretkalnina | Laura Rituma | Baiba Saulite
Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC'16)

We describe an extensive and versatile lexical resource for Latvian, an under-resourced Indo-European language, which we call Tezaurs (Latvian for ‘thesaurus’). It comprises a large explanatory dictionary of more than 250,000 entries that are derived from more than 280 external sources. The dictionary is enriched with phonetic, morphological, semantic and other annotations, as well as augmented by various language processing tools allowing for the generation of inflectional forms and pronunciation, for on-the-fly selection of corpus examples, for suggesting synonyms, etc. Tezaurs is available as a public and widely used web application for end-users, as an open data set for the use in language technology (LT), and as an API ― a set of web services for the integration into third-party applications. The ultimate goal of Tezaurs is to be the central computational lexicon for Latvian, bringing together all Latvian words and frequently used multi-word units and allowing for the integration of other LT resources and tools.

2015

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Formalising the Swedish Constructicon in Grammatical Framework
Normunds Gruzitis | Dana Dannélls | Benjamin Lyngfelt | Aarne Ranta
Proceedings of the Grammar Engineering Across Frameworks (GEAF) 2015 Workshop

2014

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Extracting a bilingual semantic grammar from FrameNet-annotated corpora
Dana Dannélls | Normunds Gruzitis
Proceedings of the Ninth International Conference on Language Resources and Evaluation (LREC'14)

We present the creation of an English-Swedish FrameNet-based grammar in Grammatical Framework. The aim of this research is to make existing framenets computationally accessible for multilingual natural language applications via a common semantic grammar API, and to facilitate the porting of such grammar to other languages. In this paper, we describe the abstract syntax of the semantic grammar while focusing on its automatic extraction possibilities. We have extracted a shared abstract syntax from ~58,500 annotated sentences in Berkeley FrameNet (BFN) and ~3,500 annotated sentences in Swedish FrameNet (SweFN). The abstract syntax defines 769 frame-specific valence patterns that cover 77,8% examples in BFN and 74,9% in SweFN belonging to the shared set of 471 frames. As a side result, we provide a unified method for comparing semantic and syntactic valence patterns across framenets.

2012

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An implementation of a Latvian resource grammar in Grammatical Framework
Pēteris Paikens | Normunds Grūzītis
Proceedings of the Eighth International Conference on Language Resources and Evaluation (LREC'12)

This paper describes an open-source Latvian resource grammar implemented in Grammatical Framework (GF), a programming language for multilingual grammar applications. GF differentiates between concrete grammars and abstract grammars: translation among concrete languages is provided via abstract syntax trees. Thus the same concrete grammar is effectively used for both language analysis and language generation. Furthermore, GF differentiates between general-purpose resource grammars and domain-specific application grammars that are built on top of the resource grammars. The GF resource grammar library (RGL) currently supports more than 20 languages that implement a common API. Latvian is the 13th official European Union language that is made available in the RGL. We briefly describe the grammatical features of Latvian and illustrate how they are handled in the multilingual framework of GF. We also illustrate some application areas of the Latvian resource grammar, and briefly discuss the limitations of the RGL and potential long-term improvements using frame semantics.

2011

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Towards a More Natural Multilingual Controlled Language Interface to OWL
Normunds Gruzitis | Guntis Barzdins
Proceedings of the Ninth International Conference on Computational Semantics (IWCS 2011)

2007

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Dependency-Based Hybrid Model of Syntactic Analysis for the Languages with a Rather Free Word Order
Guntis Bārzdiņš | Normunds Grūzītis | Gunta Nešpore | Baiba Saulīte
Proceedings of the 16th Nordic Conference of Computational Linguistics (NODALIDA 2007)