Essential Speech and Language Technology for Dutch: Results by the STEVIN-programme

Computational Linguistics; Germanic Languages; Artificial Intelligence (incl. Robotics); Computing Methodologie

The pronoun interpretation problem in Italian complex predicates

This thesis explores the syntactic and pragmatic factors involved in the interpretation of clitic pronouns in Principle B contexts in both theoretical and acquisition perspective. The Pronoun Interpretation Problem, i.e. children’s apparent difficulty with the application of Principle B, defines a stage lasting up to about age 6: (1) Mama Beari is washing heri (50% correct at age 5;6) (2) Lo gnomoi lo*i lava (85% correct at age 4;8) Italian The gnome him.washes It is assumed that clitic pronouns like lo are exempted from interpretation problems because they can only be interpreted via binding. Romance children, however, show interpretation problems in complex sentences like (3): (3) La niñai lai ve bailar (64% correct at age 5;6) Sentences like the above, which involve Exceptional Case Marking, are the main focus of the present research. We maintain that (3) can only be explained if Principle B does not apply to these structures, as also proposed by Reinhart and Reuland’s (1993) and Reuland’s (2001) alternative binding theories. In order to explain (i) why clitics can only be interpreted via binding in simple sentences like (2) and (ii) why binding does not apply to (3), we draw on two fundamental assumptions: (i) binding effects in object cliticization are the output of the narrow syntactic derivation, specifically, of movement to the left edge of v*P; (ii) under a phase‐based model of syntactic derivations (Chomsky 2001), the binding domain is not the sentence, but the vP phase. We argue that the derivation in (3) contains an unbound occurrence of the pronoun, which allows children to covalue the matrix subject and the pronoun in pragmatics; such hypothesis receives support by our experimental finding that another complex predicate in Italian, causative faire‐par, triggers PIP. Ultimately, we suggest that the PIP can be ascribed to a unitary cause across languages, namely, the delayed pragmatic acquisition of local coreference

Coherence in Machine Translation

Coherence ensures individual sentences work together to form a meaningful document. When properly translated, a coherent document in one language should result in a coherent document in another language. In Machine Translation, however, due to reasons of modeling and computational complexity, sentences are pieced together from words or phrases based on short context windows and with no access to extra-sentential context. In this thesis I propose ways to automatically assess the coherence of machine translation output. The work is structured around three dimensions: entity-based coherence, coherence as evidenced via syntactic patterns, and coherence as evidenced via discourse relations. For the first time, I evaluate existing monolingual coherence models on this new task, identifying issues and challenges that are specific to the machine translation setting. In order to address these issues, I adapted a state-of-the-art syntax model, which also resulted in improved performance for the monolingual task. The results clearly indicate how much more difficult the new task is than the task of detecting shuffled texts. I proposed a new coherence model, exploring the crosslingual transfer of discourse relations in machine translation. This model is novel in that it measures the correctness of the discourse relation by comparison to the source text rather than to a reference translation. I identified patterns of incoherence common across different language pairs, and created a corpus of machine translated output annotated with coherence errors for evaluation purposes. I then examined lexical coherence in a multilingual context, as a preliminary study for crosslingual transfer. Finally, I determine how the new and adapted models correlate with human judgements of translation quality and suggest that improvements in general evaluation within machine translation would benefit from having a coherence component that evaluated the translation output with respect to the source text

Dutch A-Scrambling Is Not Movement: Evidence from Antecedent Priming

The present study focuses on A-scrambling in Dutch, a local word-order alternation that typically signals the discourse-anaphoric status of the scrambled constituent. We use cross-modal priming to investigate whether an A-scrambled direct object gives rise to antecedent reactivation effects in the position where a movement theory would postulate a trace. Our results indicate that this is not the case, suggesting that A-scrambling in Dutch results from variation in base-generated order

読み方の定量的分析に基づく個人およびテキストの特徴認識

学位の種別:課程博士University of Tokyo(東京大学

Caught in the middle – language use and translation : a festschrift for Erich Steiner on the occasion of his 60th birthday

This book celebrates Erich Steiner’s scholarly work. In 25 contributions, colleagues and friends take up issues closely related to his research interests in linguistics and translation studies. The result is a colourful kaleidoscope reflecting the many strands of research questions that Erich Steiner helped advance in the past decades and the cheerful, inspiring atmosphere he continues to create

Word Sense Consistency in Statistical and Neural Machine Translation

Different senses of source words must often be rendered by different words in the target language when performing machine translation (MT). Selecting the correct translation of polysemous words can be done based on the contexts of use. However, state-of-the-art MT algorithms generally work on a sentence-by-sentence basis that ignores information across sentences. In this thesis, we address this problem by studying novel contextual approaches to reduce source word ambiguity in order to improve translation quality. The thesis consists of two parts: the first part is devoted to methods for correcting ambiguous word translations by enforcing consistency across sentences, and the second part investigates sense-aware MT systems that address the ambiguity problem for each word. In the first part, we propose to reduce word ambiguity by using lexical consistency, starting from the one-sense-per-discourse hypothesis. If a polysemous word appears multiple times in a discourse, it is likely that occurrences will share the same sense. We first improve the translation of polysemous nouns (Y) in the case when a previous occurrence of a noun as the head of a compound noun phrase (XY) is available in a text. Experiments on two language pairs show that the translations of the targeted polysemous nouns are significantly improved. As compound pairs X Y /Y appear quite infrequently in texts, we extend our work by analysing the repetition of nouns which are not compounds. We propose a method to decide whether two occurrences of the same noun in a source text should be translated consistently. We design a classifier to predict translation consistency based on syntactic and semantic features. We integrate the classifiersâ output into MT. We experiment on two language pairs and show that our method closes up to 50% of the gap in BLEU scores between the baseline and an oracle classifier. In the second part of the thesis, we design sense-aware MT systems that (automatically) select the correct translations of ambiguous words by performing word sense disambiguation (WSD). We demonstrate that WSD can improve MT by widening the source context considered when modeling the senses of potentially ambiguous words. We first design three adaptive clustering algorithms, respectively based on k-means, Chinese restaurant process and random walk. For phrase-based statistical MT, we integrate the sense knowledge as an additional feature through a factored model and show that the combination improves the translation from English to five other languages. As the sense integration appears promising for SMT, we also transfer this approach to the newer neural MT models, which are now state of the art. However, unlike SMT, for which it is easier to use linguistic features, NMT uses vectors for word generation and traditional feature incorporation does not work here. We design a sense-aware NMT model that jointly learns the sense knowledge using an attention-based sense selection mechanism and concatenates the learned sense vectors with word vectors during encoding . Such a concatenation outperforms several baselines. The improvements are significant over both overall and analysed ambiguous words over the same language pairs we experiment with SMT. Overall, the thesis proves that lexical consistency and WSD are practical and workable solutions that lead to global improvements in translation in ranges of 0.2 to 1.5 BLEU score

Control in free adjuncts: the 'dangling modifier' in English

In this dissertation, I present an account of the control of free adjuncts that relies on incremental processing. While many free adjuncts are controlled by the subject of the matrix clause (1a), this is not always the case. Some seem to be controlled by non-subject elements within the matrix clause (1b), others are apparently controlled by the discourse topic (1c), and still others involve the perceiver of the matrix clause in logophoric control (1d). These control patterns have raised the ire of many grammatical prescriptivists, who often label such constructions as ‘danglers’. (1) a. Turning the corner on his motorcycle, he saw a church. b. Turning the corner on his motorcycle, his grip began to slip. c. While under development, they put all other projects on hold. d. Turning the corner on my motorcycle, a church came into view. There have been several explanations of these patterns. Many researchers see free adjuncts as obligatorily controlled by the subject (1a) except where this is not possible, in which case logophoric control arises (1b,d). But such approaches cannot account for (1c), in which the controller is inanimate and thus incapable of perceiving anything. Other researchers regard non-subject control as the result of either an attempt to establish semantic coherence between two apparently unrelated clauses or an exhaustive search for alternative controllers based on a complex set of syntactic, semantic, and pragmatic clues. These approaches predict processing difficulty whenever a mismatch occurs, but most language users process sentences like (1b-d) fairly easily. My central claim is that the patterns found in adjunct control arise because the establishment of control continues throughout the process of understanding a given sentence. The language user, on encountering a free adjunct, guesses at a suitable controller. Disruption occurs when another potential controller arrives that is at least as adequate as the current guess. I support this claim through analysis of an extensive collection of attested examples, taking care to cover the relevant syntactic, semantic, pragmatic, and processing facts. I also emphasise how important it is for theoretical and descriptive studies to make specific predictions that could in principle be vindicated or falsified by future work in historical syntax or experimental psycholinguistics