96 research outputs found

    Acoustic Modelling for Under-Resourced Languages

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    Automatic speech recognition systems have so far been developed only for very few languages out of the 4,000-7,000 existing ones. In this thesis we examine methods to rapidly create acoustic models in new, possibly under-resourced languages, in a time and cost effective manner. For this we examine the use of multilingual models, the application of articulatory features across languages, and the automatic discovery of word-like units in unwritten languages

    24th Nordic Conference on Computational Linguistics (NoDaLiDa)

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    A Study of the Variation and Change in the Vowels of the Achterhoeks Dialect

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    The Achterhoeks dialect, spoken in the eastern Dutch province of Gelderland near the German border, is a Low Saxon dialect that differs noticeably from Standard Dutch in all linguistic areas. Previous research has comprehensively covered the differences in lexicon (see, for example, Schaars, 1984; Van Prooije, 2011), but less has been done on the phonology in this area (the most notable exception being Kloeke, 1927). There has been research conducted on the changes observed in other Dutch dialects, such as Brabants (Hagen, 1987; Swanenberg, 2009) and Limburgs (Hinskens, 1992), but not so much in Achterhoeks, and whether the trends observed in other dialects are also occurring in the Achterhoek area. It is claimed that the regional Dutch dialects are slowly converging towards the standard variety (Wieling, Nerbonne & Baayen, 2011), and this study aims to not only fill some of the gaps in Achterhoeks dialectology, but also to test to what extent the vowels are converging on the standard. This research examines changes in six lexical sets from 1979 to 2015 in speakers’ conscious representation of dialect. This conscious representation was an important aspect of the study, as what it means to speak in dialect may differ from person to person, and so the salience of vowels can be measured based on the number of their occurrences in self-described dialectal speech. Through a perception task, this research also presents a view of the typical Achterhoeks speaker as seen by other Dutch speakers, in order to provide a sociolinguistic explanation for the initial descriptive account of any vowel change observed in dialectal speech. Subtle changes in the Achterhoeks vowels were observed, suggesting a lack of stability, but not yet at the stage of functional dialect loss. The most noticeable difference within the Achterhoek area occurs with the pronunciation of what we term the HUIS vowel when it appears after /r/, realised as either [u] or [y]. The lexical sets of PRAAT, KAART, and KAAS were presented in three groups: as front, Standard and back vowels, with pronunciation patterns attributed to post-Westphalian breaking processes, grammatical rules, and trajectories associated with the original West Germanic vowels. The accompanying perception study provided a partner to the main research, suggesting subconscious social information behind what it means to speak in dialect

    Models and Analysis of Vocal Emissions for Biomedical Applications

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    The International Workshop on Models and Analysis of Vocal Emissions for Biomedical Applications (MAVEBA) came into being in 1999 from the particularly felt need of sharing know-how, objectives and results between areas that until then seemed quite distinct such as bioengineering, medicine and singing. MAVEBA deals with all aspects concerning the study of the human voice with applications ranging from the neonate to the adult and elderly. Over the years the initial issues have grown and spread also in other aspects of research such as occupational voice disorders, neurology, rehabilitation, image and video analysis. MAVEBA takes place every two years always in Firenze, Italy. This edition celebrates twenty years of uninterrupted and succesfully research in the field of voice analysis

    CHORUS Deliverable 2.1: State of the Art on Multimedia Search Engines

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    Based on the information provided by European projects and national initiatives related to multimedia search as well as domains experts that participated in the CHORUS Think-thanks and workshops, this document reports on the state of the art related to multimedia content search from, a technical, and socio-economic perspective. The technical perspective includes an up to date view on content based indexing and retrieval technologies, multimedia search in the context of mobile devices and peer-to-peer networks, and an overview of current evaluation and benchmark inititiatives to measure the performance of multimedia search engines. From a socio-economic perspective we inventorize the impact and legal consequences of these technical advances and point out future directions of research

    Discriminative connectionist approaches for automatic speech recognition in cars

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    The first part of this thesis is devoted to the evaluation of approaches which exploit the inherent redundancy of the speech signal to improve the noise robustness. On the basis of this evaluation on the AURORA 2000 database, we further study in detail two of the evaluated approaches. The first of these approaches is the hybrid RBF/HMM approach, which is an attempt to combine the superior classification performance of radial basis functions (RBFs) with the ability of HMMs to model time variation. The second approach is using neural networks to non-linearly reduce the dimensionality of large feature vectors including context frames. We propose the use of different MLP topologies for that purpose. Experiments on the AURORA 2000 database reveal that the performance of the first approach is similar to the performance of systems based on SCHMMs. The second approach cannot outperform the performance of linear discriminant analysis (LDA) on a database recorded in real car environments, but it is on average significantly better than LDA on the AURORA 2000 database.Im ersten Teil dieser Arbeit werden bestehende Verfahren zur Erhöhung der Robustheit von Spracherkennungssystemen in lauten Umgebungen evaluiert, die auf der Ausnutzung der Redundanz im Sprachsignal basieren. Auf der Grundlage dieser Evaluation auf der AURORA 2000 Datenbank werden zwei spezielle Ansätze weiter ausgearbeitet und detalliert analysiert. Der erste dieser Ansätze verbindet die herausragende Klassifikationsleistung von neuronalen Netzen mit radialen Basisfunktionen (RBF) mit der Fähigkeit von Hidden-Markov-Modellen (HMM), Zeitveränderlichkeiten zu modellieren. In einem zweiten Ansatz werden NN zur nichtlinearen Dimensionsreduktion hochdimensionaler Kontextvektoren in unterschiedlichen Netzwerk-Topologien untersucht. In Experimenten konnte gezeigt werden, dass der erste dieser Ansätze für die AURORA-Datenbank eine ähnliche Leistungsfähigkeit wie semikontinuierliche HMM (SCHMM) aufweist. Der zweite Ansatz erzielt auf einer im Kraftfahrzeug aufgenommenen Datenbank keine Verbesserung gegenüber den klassischen linearen Ansätzen zu Dimensionsreduktion (LDA), erweist sich aber auf der AURORA-Datenbank als signifikan

    Proceedings of the Eighth Italian Conference on Computational Linguistics CliC-it 2021

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    The eighth edition of the Italian Conference on Computational Linguistics (CLiC-it 2021) was held at Università degli Studi di Milano-Bicocca from 26th to 28th January 2022. After the edition of 2020, which was held in fully virtual mode due to the health emergency related to Covid-19, CLiC-it 2021 represented the first moment for the Italian research community of Computational Linguistics to meet in person after more than one year of full/partial lockdown

    Proceedings

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    Proceedings of the Ninth International Workshop on Treebanks and Linguistic Theories. Editors: Markus Dickinson, Kaili Müürisep and Marco Passarotti. NEALT Proceedings Series, Vol. 9 (2010), 268 pages. © 2010 The editors and contributors. Published by Northern European Association for Language Technology (NEALT) http://omilia.uio.no/nealt . Electronically published at Tartu University Library (Estonia) http://hdl.handle.net/10062/15891

    Re-examining Phonological and Lexical Correlates of Second Language Comprehensibility:The Role of Rater Experience

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    Few researchers and teachers would disagree that some linguistic aspects of second language (L2) speech are more crucial than others for successful communication. Underlying this idea is the assumption that communicative success can be broadly defined in terms of speakers’ ability to convey the intended meaning to the interlocutor, which is frequently captured through a listener-based rating of comprehensibility or ease of understanding (e.g. Derwing & Munro, 2009; Levis, 2005). Previous research has shown that communicative success – for example, as defined through comprehensible L2 speech – depends on several linguistic dimensions of L2 output, including its segmental and suprasegmental pronunciation, fluency-based characteristics, lexical and grammatical content, as well as discourse structure (e.g. Field, 2005; Hahn, 2004; Kang et al., 2010; Trofimovich & Isaacs, 2012). Our chief objective in the current study was to explore the L2 comprehensibility construct from a language assessment perspective (e.g. Isaacs & Thomson, 2013), by targeting rater experience as a possible source of variance influencing the degree to which raters use various characteristics of speech in judging L2 comprehensibility. In keeping with this objective, we asked the following question: What is the extent to which linguistic aspects of L2 speech contributing to comprehensibility ratings depend on raters’ experience

    European Language Grid

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    This open access book provides an in-depth description of the EU project European Language Grid (ELG). Its motivation lies in the fact that Europe is a multilingual society with 24 official European Union Member State languages and dozens of additional languages including regional and minority languages. The only meaningful way to enable multilingualism and to benefit from this rich linguistic heritage is through Language Technologies (LT) including Natural Language Processing (NLP), Natural Language Understanding (NLU), Speech Technologies and language-centric Artificial Intelligence (AI) applications. The European Language Grid provides a single umbrella platform for the European LT community, including research and industry, effectively functioning as a virtual home, marketplace, showroom, and deployment centre for all services, tools, resources, products and organisations active in the field. Today the ELG cloud platform already offers access to more than 13,000 language processing tools and language resources. It enables all stakeholders to deposit, upload and deploy their technologies and datasets. The platform also supports the long-term objective of establishing digital language equality in Europe by 2030 – to create a situation in which all European languages enjoy equal technological support. This is the very first book dedicated to Language Technology and NLP platforms. Cloud technology has only recently matured enough to make the development of a platform like ELG feasible on a larger scale. The book comprehensively describes the results of the ELG project. Following an introduction, the content is divided into four main parts: (I) ELG Cloud Platform; (II) ELG Inventory of Technologies and Resources; (III) ELG Community and Initiative; and (IV) ELG Open Calls and Pilot Projects
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