142 research outputs found
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
Examining lexical coherence in a multilingual setting
This paper presents a preliminary study of lexical coherence and cohesion in the context of multiple languages.
We explore two entity-based frameworks in a multilingual setting in an attempt to understand how lexical coherence is realised across different languages. These frameworks (an entity-grid model and an entity graph metric) have previously been used for assessing coherence in a monolingual setting. We apply them to a multilingual setting for the first time, assessing whether entity based coherence frameworks could help ensure lexical coherence in a Machine Translation context
New perspectives on cohesion and coherence: Implications for translation
The contributions to this volume investigate relations of cohesion and coherence as well as instantiations of discourse phenomena and their interaction with information structure in multilingual contexts. Some contributions concentrate on procedures to analyze cohesion and coherence from a corpus-linguistic perspective. Others have a particular focus on textual cohesion in parallel corpora that include both originals and translated texts. Additionally, the papers in the volume discuss the nature of cohesion and coherence with implications for human and machine translation.The contributors are experts on discourse phenomena and textuality who address these issues from an empirical perspective. The chapters in this volume are grounded in the latest research making this book useful to both experts of discourse studies and computational linguistics, as well as advanced students with an interest in these disciplines. We hope that this volume will serve as a catalyst to other researchers and will facilitate further advances in the development of cost-effective annotation procedures, the application of statistical techniques for the analysis of linguistic phenomena and the elaboration of new methods for data interpretation in multilingual corpus linguistics and machine translation
New perspectives on cohesion and coherence: Implications for translation
The contributions to this volume investigate relations of cohesion and coherence as well as instantiations of discourse phenomena and their interaction with information structure in multilingual contexts. Some contributions concentrate on procedures to analyze cohesion and coherence from a corpus-linguistic perspective. Others have a particular focus on textual cohesion in parallel corpora that include both originals and translated texts. Additionally, the papers in the volume discuss the nature of cohesion and coherence with implications for human and machine translation.The contributors are experts on discourse phenomena and textuality who address these issues from an empirical perspective. The chapters in this volume are grounded in the latest research making this book useful to both experts of discourse studies and computational linguistics, as well as advanced students with an interest in these disciplines. We hope that this volume will serve as a catalyst to other researchers and will facilitate further advances in the development of cost-effective annotation procedures, the application of statistical techniques for the analysis of linguistic phenomena and the elaboration of new methods for data interpretation in multilingual corpus linguistics and machine translation
New perspectives on cohesion and coherence: Implications for translation
The contributions to this volume investigate relations of cohesion and coherence as well as instantiations of discourse phenomena and their interaction with information structure in multilingual contexts. Some contributions concentrate on procedures to analyze cohesion and coherence from a corpus-linguistic perspective. Others have a particular focus on textual cohesion in parallel corpora that include both originals and translated texts. Additionally, the papers in the volume discuss the nature of cohesion and coherence with implications for human and machine translation.The contributors are experts on discourse phenomena and textuality who address these issues from an empirical perspective. The chapters in this volume are grounded in the latest research making this book useful to both experts of discourse studies and computational linguistics, as well as advanced students with an interest in these disciplines. We hope that this volume will serve as a catalyst to other researchers and will facilitate further advances in the development of cost-effective annotation procedures, the application of statistical techniques for the analysis of linguistic phenomena and the elaboration of new methods for data interpretation in multilingual corpus linguistics and machine translation
Identifying Semantic Divergences in Parallel Text without Annotations
Recognizing that even correct translations are not always semantically
equivalent, we automatically detect meaning divergences in parallel sentence
pairs with a deep neural model of bilingual semantic similarity which can be
trained for any parallel corpus without any manual annotation. We show that our
semantic model detects divergences more accurately than models based on surface
features derived from word alignments, and that these divergences matter for
neural machine translation.Comment: Accepted as a full paper to NAACL 201
New perspectives on cohesion and coherence: Implications for translation
The contributions to this volume investigate relations of cohesion and coherence as well as instantiations of discourse phenomena and their interaction with information structure in multilingual contexts. Some contributions concentrate on procedures to analyze cohesion and coherence from a corpus-linguistic perspective. Others have a particular focus on textual cohesion in parallel corpora that include both originals and translated texts. Additionally, the papers in the volume discuss the nature of cohesion and coherence with implications for human and machine translation.The contributors are experts on discourse phenomena and textuality who address these issues from an empirical perspective. The chapters in this volume are grounded in the latest research making this book useful to both experts of discourse studies and computational linguistics, as well as advanced students with an interest in these disciplines. We hope that this volume will serve as a catalyst to other researchers and will facilitate further advances in the development of cost-effective annotation procedures, the application of statistical techniques for the analysis of linguistic phenomena and the elaboration of new methods for data interpretation in multilingual corpus linguistics and machine translation
New perspectives on cohesion and coherence: Implications for translation
The contributions to this volume investigate relations of cohesion and coherence as well as instantiations of discourse phenomena and their interaction with information structure in multilingual contexts. Some contributions concentrate on procedures to analyze cohesion and coherence from a corpus-linguistic perspective. Others have a particular focus on textual cohesion in parallel corpora that include both originals and translated texts. Additionally, the papers in the volume discuss the nature of cohesion and coherence with implications for human and machine translation.The contributors are experts on discourse phenomena and textuality who address these issues from an empirical perspective. The chapters in this volume are grounded in the latest research making this book useful to both experts of discourse studies and computational linguistics, as well as advanced students with an interest in these disciplines. We hope that this volume will serve as a catalyst to other researchers and will facilitate further advances in the development of cost-effective annotation procedures, the application of statistical techniques for the analysis of linguistic phenomena and the elaboration of new methods for data interpretation in multilingual corpus linguistics and machine translation
New perspectives on cohesion and coherence: Implications for translation
The contributions to this volume investigate relations of cohesion and coherence as well as instantiations of discourse phenomena and their interaction with information structure in multilingual contexts. Some contributions concentrate on procedures to analyze cohesion and coherence from a corpus-linguistic perspective. Others have a particular focus on textual cohesion in parallel corpora that include both originals and translated texts. Additionally, the papers in the volume discuss the nature of cohesion and coherence with implications for human and machine translation.The contributors are experts on discourse phenomena and textuality who address these issues from an empirical perspective. The chapters in this volume are grounded in the latest research making this book useful to both experts of discourse studies and computational linguistics, as well as advanced students with an interest in these disciplines. We hope that this volume will serve as a catalyst to other researchers and will facilitate further advances in the development of cost-effective annotation procedures, the application of statistical techniques for the analysis of linguistic phenomena and the elaboration of new methods for data interpretation in multilingual corpus linguistics and machine translation
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