Methods and algorithms for unsupervised learning of morphology

This is an accepted manuscript of a chapter published by Springer in Computational Linguistics and Intelligent Text Processing. CICLing 2014. Lecture Notes in Computer Science, vol 8403 in 2014 available online: https://doi.org/10.1007/978-3-642-54906-9_15 The accepted version of the publication may differ from the final published version.This paper is a survey of methods and algorithms for unsupervised learning of morphology. We provide a description of the methods and algorithms used for morphological segmentation from a computational linguistics point of view. We survey morphological segmentation methods covering methods based on MDL (minimum description length), MLE (maximum likelihood estimation), MAP (maximum a posteriori), parametric and non-parametric Bayesian approaches. A review of the evaluation schemes for unsupervised morphological segmentation is also provided along with a summary of evaluation results on the Morpho Challenge evaluations.Published versio

A System for Simultaneous Translation of Lectures and Speeches

This thesis realizes the first existing automatic system for simultaneous speech-to-speech translation. The focus of this system is the automatic translation of (technical oriented) lectures and speeches from English to Spanish, but the different aspects described in this thesis will also be helpful for developing simultaneous translation systems for other domains or languages

Proceedings of the 17th Annual Conference of the European Association for Machine Translation

Proceedings of the 17th Annual Conference of the European Association for Machine Translation (EAMT

GREC: Multi-domain Speech Recognition for the Greek Language

Μία από τις κορυφαίες προκλήσεις στην Αυτόματη Αναγνώριση Ομιλίας είναι η ανάπτυξη ικανών συστημάτων που μπορούν να έχουν ισχυρή απόδοση μέσα από διαφορετικές συνθήκες ηχογράφησης. Στο παρόν έργο κατασκευάζουμε και αναλύουμε το GREC, μία μεγάλη πολυτομεακή συλλογή δεδομένων για αυτόματη αναγνώριση ομιλίας στην ελληνική γλώσσα. Το GREC αποτελείται από τρεις βάσεις δεδομένων στους θεματικούς τομείς των «εκπομπών ειδήσεων», «ομιλίας από δωρισμένες εγγραφές φωνής», «ηχητικών βιβλίων» και μιας νέας συλλογής δεδομένων στον τομέα των «πολιτικών ομιλιών». Για τη δημιουργία του τελευταίου, συγκεντρώνουμε δεδομένα ομιλίας από ηχογραφήσεις των επίσημων συνεδριάσεων της Βουλής των Ελλήνων, αποδίδοντας ένα σύνολο δεδομένων που αποτελείται από 120 ώρες ομιλίας πολιτικού περιεχομένου. Περιγράφουμε με λεπτομέρεια την καινούρια συλλογή δεδομένων, την προεπεξεργασία και την ευθυγράμμιση ομιλίας, τα οποία βασίζονται στο εργαλείο ανοιχτού λογισμικού Kaldi. Επιπλέον, αξιολογούμε την απόδοση των μοντέλων Gaussian Mixture (GMM) - Hidden Markov (HMM) και Deep Neural Network (DNN) - HMM όταν εφαρμόζονται σε δεδομένα από διαφορετικούς τομείς. Τέλος, προσθέτουμε τη δυνατότητα αυτόματης δεικτοδότησης ομιλητών στο Kaldi-gRPC-Server, ενός εργαλείου γραμμένο σε Python που βασίζεται στο PyKaldi και στο gRPC για βελτιωμένη ανάπτυξη μοντέλων αυτόματης αναγνώρισης ομιλίας.One of the leading challenges in Automatic Speech Recognition (ASR) is the development of robust systems that can perform well under multiple settings. In this work we construct and analyze GREC, a large, multi-domain corpus for automatic speech recognition for the Greek language. GREC is a collection of three available subcorpora over the domains of “news casts”, “crowd-sourced speech”, “audiobooks”, and a new corpus in the domain of “public speeches”. For the creation of the latter, HParl, we collect speech data from recordings of the official proceedings of the Hellenic Parliament, yielding, a dataset which consists of 120 hours of political speech segments. We describe our data collection, pre-processing and alignment setup, which are based on Kaldi toolkit. Furthermore, we perform extensive ablations on the recognition performance of Gaussian Mixture (GMM) - Hidden Markov (HMM) models and Deep Neural Network (DNN) - HMM models over the different domains. Finally, we integrate speaker diarization features to Kaldi-gRPC-Server, a modern, pythonic tool based on PyKaldi and gRPC for streamlined deployment of Kaldi based speech recognition

Concordancing Software in Practice: An investigation of searches and translation problems across EU official languages

2011/2012The present work reports on an empirical study aimed at investigating translation problems across multiple language pairs. In particular, the analysis is aimed at developing a methodological approach to study concordance search logs taken as manifestations of translation problems and, in a wider perspective, information needs. As search logs are a relatively unexplored data type within translation process research, a controlled environment was needed in order to carry out this exploratory analysis without incurring in additional problems caused by an excessive amount of variables. The logs were collected at the European Commission and contain a large volume of searches from English into 20 EU languages that staff translators working for the EU translation services submitted to an internally available multilingual concordancer. The study attempts to (i) identify differences in the searches (i.e. problems) based on the language pairs; and (ii) group problems into types. Furthermore, the interactions between concordance users and the tool itself have been examined to provide a translation-oriented perspective on the domain of Human-Computer Interaction. The study draws on the literature on translation problems, Information Retrieval and Web search log analysis, moving from the assumption that in the perspective of concordance searching, translation problems are best interpreted as information needs for which the concordancer is chosen as a form of external support. The structure of a concordance search is examined in all its parts and is eventually broken down into two main components: the 'Search Strategy' component and the 'Problem Unit' component. The former was further analyzed using a mainly quantitative approach, whereas the latter was addressed from a more qualitative perspective. The analysis of the Problem Unit takes into account the length of the search strings as well as their content and linguistic form, each addressed with a different methodological approach. Based on the understanding of concordance searches as manifestations of translation problems, a user- centered classification of translation-oriented information needs is developed to account for as many "problem" scenarios as possible. According to the initial expectations, different languages should experience different problems. This assumption could not be verified: the 20 different language pairs considered in this study behaved consistently on many levels and, due to the specific research environment, no definite conclusions could be reached as regards the role of the language family criterion for problem identification. The analysis of the 'Problem Unit' component has highlighted automatized support for translating Named Entities as a possible area for further research in translation technology and the development of computer-based translation support tools. Finally, the study indicates (concordance) search logs as an additional data type to be used in experiments on the translation process and for triangulation purposes, while drawing attention on the concordancer as a type of translation aid to be further fine-tuned for the needs of professional translators. ***Il presente lavoro consiste in uno studio empirico sui problemi di traduzione che emergono quando si considerano diverse coppie di lingue e in particolare sviluppa una metodologia per analizzare i log di ricerche effettuate dai traduttori in un software di concordanza (concordancer) quali manifestazioni di problemi di traduzione che, visti in una prospettiva più ampia, si possono anche considerare dei "bisogni d'informazione" (information needs). I log di ricerca costituiscono una tipologia di dato ancora relativamente nuova e inesplorata nell'ambito delle ricerche sul processo di traduzione e pertanto è emersa la necessità di svolgere un'analisi di tipo esplorativo in un contesto controllato onde evitare le problematiche aggiuntive derivanti da un numero eccessivo di variabili. I log di ricerca sono stati raccolti presso la Commissione europea e contengono quantitativi ingenti di ricerche effettuate dai traduttori impiegati presso i servizi di traduzione dell'Unione europea in un concordancer multilingue disponibile come risorsa interna. L'analisi si propone di individuare le differenze nelle ricerche (e quindi nei problemi) a seconda della coppia di lingue selezionata e di raggruppare tali problemi in tipologie. Lo studio fornisce inoltre informazioni sulle modalità di interazione tra gli utenti e il software nell'ambito di un contesto traduttivo, contribuendo alla ricerca nel campo dell'interazione uomo-macchina (Human-Computer Interaction). Il presente studio trae spunto dalla letteratura sui problemi di traduzione, sull'estrazione d'informazioni (Information Retrieval) e sulle ricerche nel Web e si propone di considerare i problemi di traduzione associati all'impiego di uno strumento per le concordanze quali bisogni di informazione per i quali lo strumento di concordanze è stato scelto come forma di supporto esterna. Ogni singola ricerca è stata esaminata e scomposta in due elementi principali: la "strategia di ricerca" (Search Strategy) e l'"unità problematica" (Problem Unit) che vengono studiati rispettivamente usando approcci prevalentemente di tipo quantitativo e qualitativo. L'analisi dell'unità problematica prende in considerazione la lunghezza, il contenuto e la forma linguistica delle stringhe, analizzando ciascuna con una metodologia di lavoro appositamente studiata. Avendo interpretato le ricerche di concordanze quali manifestazioni di bisogni d'informazione, l'analisi prosegue con la definizione di una serie di categorie di bisogni d'informazione (o problemi) legati alla traduzione e incentrati sul singolo utente al fine di includere quanti più scenari di ricerca possibile. L'assunto iniziale in base al quale lingue diverse manifesterebbero problemi diversi non è stato verificato empiricamente in quanto le 20 coppie di lingue esaminate hanno mostrato comportamenti alquanto similari nei diversi livelli di analisi. Vista la peculiarità dei dati utilizzati e la specificità dell'Unione europea come contesto di ricerca, non è stato possibile ottenere conclusioni definitive in merito al ruolo delle famiglie linguistiche quali indicatori di problemi, rispetto ad altri criteri di classificazione. L'analisi dell'unità problematica ha evidenziato le entità denominate (Named Entities) quale possibile oggetto di futuri progetti di ricerca nell'ambito delle tecnologie della traduzione. Oltre a offrire un contributo per i futuri sviluppi nell'ambito dei supporti informatici alla traduzione, con il presente studio si è voluto altresì presentare i log delle ricerche (di concordanze) quale tipologia aggiuntiva di dati per lo studio del processo di traduzione e per la triangolazione dei risultati empirico-sperimentali, cercando anche di suggerire possibili tratti migliorativi dei software di concordanza sulla base dei bisogni di informazione riscontrati nei traduttori.XXV Ciclo198

Computational approaches to semantic change (Volume 6)

Semantic change — how the meanings of words change over time — has preoccupied scholars since well before modern linguistics emerged in the late 19th and early 20th century, ushering in a new methodological turn in the study of language change. Compared to changes in sound and grammar, semantic change is the least understood. Ever since, the study of semantic change has progressed steadily, accumulating a vast store of knowledge for over a century, encompassing many languages and language families. Historical linguists also early on realized the potential of computers as research tools, with papers at the very first international conferences in computational linguistics in the 1960s. Such computational studies still tended to be small-scale, method-oriented, and qualitative. However, recent years have witnessed a sea-change in this regard. Big-data empirical quantitative investigations are now coming to the forefront, enabled by enormous advances in storage capability and processing power. Diachronic corpora have grown beyond imagination, defying exploration by traditional manual qualitative methods, and language technology has become increasingly data-driven and semantics-oriented. These developments present a golden opportunity for the empirical study of semantic change over both long and short time spans

Natural Language Processing: Integration of Automatic and Manual Analysis

There is a current trend to combine natural language analysis with research questions from the humanities. This requires an integration of automatic analysis with manual analysis, e.g. to develop a theory behind the analysis, to test the theory against a corpus, to generate training data for automatic analysis based on machine learning algorithms, and to evaluate the quality of the results from automatic analysis. Manual analysis is traditionally the domain of linguists, philosophers, and researchers from other humanities disciplines, who are often not expert programmers. Automatic analysis, on the other hand, is traditionally done by expert programmers, such as computer scientists and more recently computational linguists. It is important to bring these communities, their tools, and data closer together, to produce analysis of a higher quality with less effort. However, promising cooperations involving manual and automatic analysis, e.g. for the purpose of analyzing a large corpus, are hindered by many problems: - No comprehensive set of interoperable automatic analysis components is available. - Assembling automatic analysis components into workflows is too complex. - Automatic analysis tools, exploration tools, and annotation editors are not interoperable. - Workflows are not portable between computers. - Workflows are not easily deployable to a compute cluster. - There are no adequate tools for the selective annotation of large corpora. - In automatic analysis, annotation type systems are predefined, but manual annotation requires customizability. - Implementing new interoperable automatic analysis components is too complex. - Workflows and components are not sufficiently debuggable and refactorable. - Workflows that change dynamically via parametrization are not readily supported. - The user has no control over workflows that rely on expert skills from a different domain, undocumented knowledge, or third-party infrastructures, e.g. web services. In cooperation with researchers from the humanities, we develop innovative technical solutions and designs to facilitate the use of automatic analysis and to promote the integration of manual and automatic analysis. To address these issues, we set foundations in four areas: - Usability is improved by reducing the complexity of the APIs for building workflows and creating custom components, improving the handling of resources required by such components, and setting up auto-configuration mechanisms. - Reproducibility is improved through a concept for self-contained, portable analysis components and workflows combined with a declarative modeling approach for dynamic parametrized workflows, that facilitates avoiding unnecessary auxiliary manual steps in automatic workflows. - Flexibility is achieved by providing an extensive collection of interoperable automatic analysis components. We also compare annotation type systems used by different automatic analysis components to locate design patterns that allow for customization when used in manual analysis tasks. - Interactivity is achieved through a novel "annotation-by-query" process combining corpus search with annotation in a multi-user scenario. The process is supported by a web-based tool. We demonstrate the adequacy of our concepts through examples which represent whole classes of research problems. Additionally, we integrated all our concepts into existing open-source projects, or we implemented and published them within new open-source projects