This book provides a comprehensive overview of methods to build comparable corpora and of their applications, including machine translation, cross-lingual transfer, and various kinds of multilingual natural language processing. The authors begin with a brief history on the topic followed by a comparison to parallel resources and an explanation of why comparable corpora have become more widely used. In particular, they provide the basis for the multilingual capabilities of pre-trained models, such as BERT or GPT. The book then focuses on building comparable corpora, aligning their sentences to create a database of suitable translations, and using these sentence translations to produce dictionaries and term banks. Then, it is explained how comparable corpora can be used to build machine translation engines and to develop a wide variety of multilingual applications.

The 1990s saw a paradigm change in the use of corpus-driven methods in NLP. In the field of multilingual NLP (such as machine translation and terminology mining) this implied the use of parallel corpora. However, parallel resources are relatively scarce: many more texts are produced daily by native speakers of any given language than translated. This situation resulted in a natural drive towards the use of comparable corpora, i.e. non-parallel texts in the same domain or genre. Nevertheless, this research direction has not produced a single authoritative source suitable for researchers and students coming to the field. The proposed volume provides a reference source, identifying the state of the art in the field as well as future trends. The book is intended for specialists and students in natural language processing, machine translation and computer-assisted translation.

This book provides an overview of how comparable corpora can be used to overcome the lack of parallel resources when building machine translation systems for under-resourced languages and domains. It presents a wealth of methods and open tools for building comparable corpora from the Web, evaluating comparability and extracting parallel data that can be used for the machine translation task. It is divided into several sections, each covering a specific task such as building, processing, and using comparable corpora, focusing particularly on under-resourced language pairs and domains. The book is intended for anyone interested in data-driven machine translation for under-resourced languages and domains, especially for developers of machine translation systems, computational linguists and language workers. It offers a valuable resource for specialists and students in natural language processing, machine translation, corpus linguistics and computer-assisted translation, and promotes the broader use of comparable corpora in natural language processing and computational linguistics.

This book brings together scientists, researchers, practitioners, and students from academia and industry to present recent and ongoing research activities concerning the latest advances, techniques, and applications of natural language processing systems, and to promote the exchange of new ideas and lessons learned. Taken together, the chapters of this book provide a collection of high-quality research works that address broad challenges in both theoretical and applied aspects of intelligent natural language processing. The book presents the state-of-the-art in research on natural language processing, computational linguistics, applied Arabic linguistics and related areas. New trends in natural language processing systems are rapidly emerging – and finding application in various domains including education, travel and tourism, and healthcare, among others. Many issues encountered during the development of these applications can be resolved by incorporating language technology solutions. The topics covered by the book include: Character and Speech Recognition; Morphological, Syntactic, and Semantic Processing; Information Extraction; Information Retrieval and Question Answering; Text Classification and Text Mining; Text Summarization; Sentiment Analysis; Machine Translation Building and Evaluating Linguistic Resources; and Intelligent Language Tutoring Systems.

This volume assesses the state of the art of parallel corpus research as a whole, reporting on advances in both recent developments of parallel corpora – with some particular references to comparable corpora as well– and in ways of exploiting them for a variety of purposes. The first part of the book is devoted to new roles that parallel corpora can and should assume in translation studies and in contrastive linguistics, to the usefulness and usability of parallel corpora, and to advances in parallel corpus alignment, annotation and retrieval. There follows an up-to-date presentation of a number of parallel corpus projects currently being carried out in Europe, some of them multimodal, with certain chapters illustrating case studies developed on the basis of the corpora at hand. In most of these chapters, attention is paid to specific technical issues of corpus building. The third part of the book reflects on specific applications and on the creation of bilingual resources from parallel corpora. This volume will be welcomed by scholars, postgraduate and PhD students in the fields of contrastive linguistics, translation studies, lexicography, language teaching and learning, machine translation, and natural language processing.

This book contains papers from the Fourth International Conference on Human Language Technologies - the Baltic Perspective (Baltic HLT 2010), held in Riga in October 2010. This conference is the latest in a series which provides a forum for sharing recent advances in human language processing, and promotes cooperation between the computer science and linguistics communities of the Baltic countries and the rest of the world. Bringing together scientists, developers, providers and users, the conference is an opportunity to exchange information, discuss problems, find new synergies, and promote i.

This book provides an overview of how comparable corpora can be used to overcome the lack of parallel resources when building machine translation systems for under-resourced languages and domains. It presents a wealth of methods and open tools for building comparable corpora from the Web, evaluating comparability and extracting parallel data that can be used for the machine translation task. It is divided into several sections, each covering a specific task such as building, processing, and using comparable corpora, focusing particularly on under-resourced language pairs and domains. The book is intended for anyone interested in data-driven machine translation for under-resourced languages and domains, especially for developers of machine translation systems, computational linguists and language workers. It offers a valuable resource for specialists and students in natural language processing, machine translation, corpus linguistics and computer-assisted translation, and promotes the broader use of comparable corpora in natural language processing and computational linguistics.