Evalita\u2709 Parsing Task: comparing dependency parsers and treebanks

The aim of Evalita Parsing Task is at defining and extending Italian state of the art parsing by encouraging the application of existing models and approaches. As in the Evalita\u2707, the Task is organized around two tracks, i.e. Dependency Parsing and Constituency Parsing. As a main novelty with respect to the previous edition, the Dependency Parsing track has been articulated into two subtasks, differing at the level of the used treebanks, thus creating the prerequisites for assessing the impact of different annotation schemes on the parsers performance. In this paper, we describe the Dependency Parsing track by presenting the data sets for development and testing, reporting the test results and providing a first comparative analysis of these results, also with respect to state of the art parsing technologies

Corpora compilation for prosody-informed speech processing

Research on speech technologies necessitates spoken data, which is usually obtained through read recorded speech, and specifically adapted to the research needs. When the aim is to deal with the prosody involved in speech, the available data must reflect natural and conversational speech, which is usually costly and difficult to get. This paper presents a machine learning-oriented toolkit for collecting, handling, and visualization of speech data, using prosodic heuristic. We present two corpora resulting from these methodologies: PANTED corpus, containing 250 h of English speech from TED Talks, and Heroes corpus containing 8 h of parallel English and Spanish movie speech. We demonstrate their use in two deep learning-based applications: punctuation restoration and machine translation. The presented corpora are freely available to the research community

Annotation Schema Oriented Validation for Dependency Parsing Evaluation

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), 19-30. © 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

Multilingualism, Lingua Franca or What?

For this 10th anniversary issue we are very fortunate to have two extremely engaging conversations. They are both frank discussions on the state of the art of translation and its relevance today. We open with Henry Liu, recently President of the International Federation of Translators and close with a conversation between renowned scholars Susan Bassnett and Anthony Pym, who muse - over a glass or two - about the monster that is called ‘translation’

Statistical parsing of noun phrase structure

Noun phrases (NPs) are a crucial part of natural language, exhibiting in many cases an extremely complex structure. However, NP structure is largely ignored by the statistical parsing field, as the most widely-used corpus is not annotated with it. This lack of gold-standard data has restricted all previous efforts to parse NPs, making it impossible to perform the supervised experiments that have achieved high performance in so many Natural Language Processing (NLP) tasks. We comprehensively solve this problem by manually annotating NP structure for the entire Wall Street Journal section of the Penn Treebank. The inter-annotator agreement scores that we attain refute the belief that the task is too difficult, and demonstrate that consistent NP annotation is possible. Our gold-standard NP data is now available and will be useful for all parsers. We present three statistical methods for parsing NP structure. Firstly, we apply the Collins (2003) model, and find that its recovery of NP structure is significantly worse than its overall performance. Through much experimentation, we determine that this is not a result of the special base-NP model used by the parser, but primarily caused by a lack of lexical information. Secondly, we construct a wide-coverage, large-scale NP Bracketing system, applying a supervised model to achieve excellent results. Our Penn Treebank data set, which is orders of magnitude larger than those used previously, makes this possible for the first time. We then implement and experiment with a wide variety of features in order to determine an optimal model. Having achieved this, we use the NP Bracketing system to reanalyse NPs outputted by the Collins (2003) parser. Our post-processor outperforms this state-of-the-art parser. For our third model, we convert the NP data to CCGbank (Hockenmaier and Steedman, 2007), a corpus that uses the Combinatory Categorial Grammar (CCG) formalism. We experiment with a CCG parser and again, implement features that improve performance. We also evaluate the CCG parser against the Briscoe and Carroll (2006) reannotation of DepBank (King et al., 2003), another corpus that annotates NP structure. This supplies further evidence that parser performance is increased by improving the representation of NP structure. Finally, the error analysis we carry out on the CCG data shows that again, a lack of lexicalisation causes difficulties for the parser. We find that NPs are particularly reliant on this lexical information, due to their exceptional productivity and the reduced explicitness present in modifier sequences. Our results show that NP parsing is a significantly harder task than parsing in general. This thesis comprehensively analyses the NP parsing task. Our contributions allow wide-coverage, large-scale NP parsers to be constructed for the first time, and motivate further NP parsing research for the future. The results of our work can provide significant benefits for many NLP tasks, as the crucial information contained in NP structure is now available for all downstream systems

Abstract syntax as interlingua: Scaling up the grammatical framework from controlled languages to robust pipelines

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

Blowing in the wind: using ‘North Wind and the Sun’ texts to sample phoneme inventories

Language documentation faces a persistent and pervasive problem: How much material is enough to represent a language fully? How much text would we need to sample the full phoneme inventory of a language? In the phonetic/phonemic domain, what proportion of the phoneme inventory can we expect to sample in a text of a given length? Answering these questions in a quantifiable way is tricky, but asking them is necessary. The cumulative collection of Illustrative Texts published in the Illustration series in this journal over more than four decades (mostly renditions of the ‘North Wind and the Sun’) gives us an ideal dataset for pursuing these questions. Here we investigate a tractable subset of the above questions, namely: What proportion of a language’s phoneme inventory do these texts enable us to recover, in the minimal sense of having at least one allophone of each phoneme? We find that, even with this low bar, only three languages (Modern Greek, Shipibo and the Treger dialect of Breton) attest all phonemes in these texts. Unsurprisingly, these languages sit at the low end of phoneme inventory sizes (respectively 23, 24 and 36 phonemes). We then estimate the rate at which phonemes are sampled in the Illustrative Texts and extrapolate to see how much text it might take to display a language’s full inventory. Finally, we discuss the implications of these findings for linguistics in its quest to represent the world’s phonetic diversity, and for JIPA in its design requirements for Illustrations and in particular whether supplementary panphonic texts should be included.1 Introduction 2 Language sample 3 Data coding 3.1 Lengh/gemination 3.2 Diphthongs vs. vowel sequences 3.3 Tonal contrasts 3.4 Illustration of an Illustration: Shilluk 4 Overview of the JIPA Illustration text corpus 5 Transcript coverage 6 The nature of phoneme frequency distributions 7 Recovering the full phoneme inventory 8 Evaluating the methods against a larger corpus 9 Returning to the cross-linguistic data 10 Estimating the amount of audio needed 11 Effect on recovery of cross-linguistic frequency/rarity 12 Discussion 12.1 Recommendations for JIPA 12.2 How many data are needed to fully capture a language’s phoneme inventory? 13 Conclusio

The phonetics of speech breathing : pauses, physiology, acoustics, and perception

Speech is made up of a continuous stream of speech sounds that is interrupted by pauses and breathing. As phoneticians are primarily interested in describing the segments of the speech stream, pauses and breathing are often neglected in phonetic studies, even though they are vital for speech. The present work adds to a more detailed view of both pausing and speech breathing with a special focus on the latter and the resulting breath noises, investigating their acoustic, physiological, and perceptual aspects. We present an overview of how a selection of corpora annotate pauses and pause-internal particles, as well as a recording setup that can be used for further studies on speech breathing. For pauses, this work emphasized their optionality and variability under different tempos, as well as the temporal composition of silence and breath noise in breath pauses. For breath noises, we first focused on acoustic and physiological characteristics: We explored alignment between the onsets and offsets of audible breath noises with the start and end of expansion of both rib cage and abdomen. Further, we found similarities between speech breath noises and aspiration phases of /k/, as well as that breath noises may be produced with a more open and slightly more front place of articulation than realizations of schwa. We found positive correlations between acoustic and physiological parameters, suggesting that when speakers inhale faster, the resulting breath noises were more intense and produced more anterior in the mouth. Inspecting the entire spectrum of speech breath noises, we showed relatively flat spectra and several weak peaks. These peaks largely overlapped with resonances reported for inhalations produced with a central vocal tract configuration. We used 3D-printed vocal tract models representing four vowels and four fricatives to simulate in- and exhalations by reversing airflow direction. We found the direction to not have a general effect for all models, but only for those with high-tongue configurations, as opposed to those that were more open. Then, we compared inhalations produced with the schwa-model to human inhalations in an attempt to approach the vocal tract configuration in speech breathing. There were some similarities, however, several complexities of human speech breathing not captured in the models complicated comparisons. In two perception studies, we investigated how much information listeners could auditorily extract from breath noises. First, we tested categorizing different breath noises into six different types, based on airflow direction and airway usage, e.g. oral inhalation. Around two thirds of all answers were correct. Second, we investigated how well breath noises could be used to discriminate between speakers and to extract coarse information on speaker characteristics, such as age (old/young) and sex (female/male). We found that listeners were able to distinguish between two breath noises coming from the same or different speakers in around two thirds of all cases. Hearing one breath noise, classification of sex was successful in around 64%, while for age it was 50%, suggesting that sex was more perceivable than age in breath noises.Deutsche Forschungsgemeinschaft (DFG) – Projektnummer 418659027: "Pause-internal phonetic particles in speech communication