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Lexical And Language Modeling Of Diacritics And Morphemes In Arabic Automatic Speech Recognition
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Book Synopsis Lexical and Language Modeling of Diacritics and Morphemes in Arabic Automatic Speech Recognition by : Tuka Al Hanai
Download or read book Lexical and Language Modeling of Diacritics and Morphemes in Arabic Automatic Speech Recognition written by Tuka Al Hanai and published by . This book was released on 2014 with total page 72 pages. Available in PDF, EPUB and Kindle. Book excerpt: Arabic is a morphologically rich language which rarely displays diacritics. These two features of the language pose challenges when building Automatic Speech Recognition (ASR) systems. Morphological complexity leads to many possible combinations of stems and affixes to form words, and produces texts with high Out Of Vocabulary (OOV) rates. In addition, texts rarely display diacritics which informs the reader about short vowels, geminates, and nunnations (word ending /n/). A lack of diacritics means that 30% of textual information is missing, causing ambiguities in lexical and language modeling when attempting to model pronunciations, and the context of a particular pronunciation. Intuitively, from an English centric view, the phrase th'wrtr wrt n thwrt with 'morphological decomposition' is realized as, th wrtr wrt n th wrt. Including 'diacritics' produces, the writer wrote in the writ. Thus our investigations in this thesis are twofold. Firstly, we show the benefits and interactions between modeling all classes of diacritics (short vowels, geminates, nunnations) in the lexicon. On a Modern Standard Arabic (MSA) corpus of broadcast news, this provides a 1.9% absolute improvement in Word Error Rate (WER) (p
Book Synopsis Arabic Language Modeling with Stem-derived Morphemes for Automatic Speech Recognition by : Ilana Heintz
Download or read book Arabic Language Modeling with Stem-derived Morphemes for Automatic Speech Recognition written by Ilana Heintz and published by . This book was released on 2010 with total page 182 pages. Available in PDF, EPUB and Kindle. Book excerpt: The stem pattern derivation method is tested in the task of automatic speech recognition (ASR), and compared to three other morpheme derivation methods as well as word-based language models. We find that the utility of morphemes in increasing word accuracy scores on the ASR task is highly dependent on the ASR system's ability to accommodate the morphemes in the acoustic and pronunciation models. In experiments involving both Modern Standard Arabic and Levantine Conversational Arabic data, we find that knowledge-light methods of morpheme derivation may work as well as knowledge-rich methods. We also find that morpheme derivation methods that result in a single morpheme hypothesis per word result in stronger models than those that spread probability mass across several hypotheses per word, however, the multi-hypothesis model may be strengthened by applying informed weights to the predicted morpheme sequences. Furthermore, we exploit the flexibility of Finite State Machines, with which the stem pattern derivation method is implemented, to predict short vowels. The result is a comprehensive exploration not only of the stem pattern derivation method, but of the use of morphemes in Arabic language modeling for automatic speech recognition.
Book Synopsis Computational Linguistics, Speech And Image Processing For Arabic Language by : Neamat El Gayar
Download or read book Computational Linguistics, Speech And Image Processing For Arabic Language written by Neamat El Gayar and published by World Scientific. This book was released on 2018-09-18 with total page 286 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book encompasses a collection of topics covering recent advances that are important to the Arabic language in areas of natural language processing, speech and image analysis. This book presents state-of-the-art reviews and fundamentals as well as applications and recent innovations.The book chapters by top researchers present basic concepts and challenges for the Arabic language in linguistic processing, handwritten recognition, document analysis, text classification and speech processing. In addition, it reports on selected applications in sentiment analysis, annotation, text summarization, speech and font analysis, word recognition and spotting and question answering.Moreover, it highlights and introduces some novel applications in vital areas for the Arabic language. The book is therefore a useful resource for young researchers who are interested in the Arabic language and are still developing their fundamentals and skills in this area. It is also interesting for scientists who wish to keep track of the most recent research directions and advances in this area.
Book Synopsis Novel Techniques for Dialectal Arabic Speech Recognition by : Mohamed Elmahdy
Download or read book Novel Techniques for Dialectal Arabic Speech Recognition written by Mohamed Elmahdy and published by Springer Science & Business Media. This book was released on 2012-02-10 with total page 120 pages. Available in PDF, EPUB and Kindle. Book excerpt: Novel Techniques for Dialectal Arabic Speech describes approaches to improve automatic speech recognition for dialectal Arabic. Since speech resources for dialectal Arabic speech recognition are very sparse, the authors describe how existing Modern Standard Arabic (MSA) speech data can be applied to dialectal Arabic speech recognition, while assuming that MSA is always a second language for all Arabic speakers. In this book, Egyptian Colloquial Arabic (ECA) has been chosen as a typical Arabic dialect. ECA is the first ranked Arabic dialect in terms of number of speakers, and a high quality ECA speech corpus with accurate phonetic transcription has been collected. MSA acoustic models were trained using news broadcast speech. In order to cross-lingually use MSA in dialectal Arabic speech recognition, the authors have normalized the phoneme sets for MSA and ECA. After this normalization, they have applied state-of-the-art acoustic model adaptation techniques like Maximum Likelihood Linear Regression (MLLR) and Maximum A-Posteriori (MAP) to adapt existing phonemic MSA acoustic models with a small amount of dialectal ECA speech data. Speech recognition results indicate a significant increase in recognition accuracy compared to a baseline model trained with only ECA data.
Book Synopsis Cross-Word Modeling for Arabic Speech Recognition by : Dia AbuZeina
Download or read book Cross-Word Modeling for Arabic Speech Recognition written by Dia AbuZeina and published by Springer Science & Business Media. This book was released on 2011-11-25 with total page 82 pages. Available in PDF, EPUB and Kindle. Book excerpt: Cross-Word Modeling for Arabic Speech Recognition utilizes phonological rules in order to model the cross-word problem, a merging of adjacent words in speech caused by continuous speech, to enhance the performance of continuous speech recognition systems. The author aims to provide an understanding of the cross-word problem and how it can be avoided, specifically focusing on Arabic phonology using an HHM-based classifier.
Book Synopsis Automatic Speech Recognition of Arabic Phonemes with Neural Networks by : Mohammed Dib
Download or read book Automatic Speech Recognition of Arabic Phonemes with Neural Networks written by Mohammed Dib and published by Springer. This book was released on 2018-12-27 with total page 153 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents a contrastive linguistics study of Arabic and English for the dual purposes of improved language teaching and speech processing of Arabic via spectral analysis and neural networks. Contrastive linguistics is a field of linguistics which aims to compare the linguistic systems of two or more languages in order to ease the tasks of teaching, learning, and translation. The main focus of the present study is to treat the Arabic minimal syllable automatically to facilitate automatic speech processing in Arabic. It represents important reading for language learners and for linguists with an interest in Arabic and computational approaches.
Book Synopsis Automatic Diacritization of Arabic for Acoustic Modeling in Speech Recognition by :
Download or read book Automatic Diacritization of Arabic for Acoustic Modeling in Speech Recognition written by and published by . This book was released on 2004 with total page 9 pages. Available in PDF, EPUB and Kindle. Book excerpt: Automatic recognition of Arabic dialectal speech is a challenging task because Arabic dialects are essentially spoken varieties. Only few dialectal resources are available to date; moreover, most available acoustic data collections are transcribed without diacritics. Such a transcription omits essential pronunciation information about a word, such as short vowels. In this paper we investigate various procedures that enable us to use such training data by automatically inserting the missing diacritics into the transcription. These procedures use acoustic information in combination with different levels of morphological and contextual constraints. We evaluate their performance against manually diacritized transcriptions. In addition, we demonstrate the effect of their accuracy on the recognition performance of acoustic models trained on automatically diacritized training data.
Book Synopsis Analysis and Application of Natural Language and Speech Processing by : Mourad Abbas
Download or read book Analysis and Application of Natural Language and Speech Processing written by Mourad Abbas and published by Springer Nature. This book was released on 2023-02-22 with total page 217 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents recent advances in NLP and speech technology, a topic attracting increasing interest in a variety of fields through its myriad applications, such as the demand for speech guided touchless technology during the Covid-19 pandemic. The authors present results of recent experimental research that provides contributions and solutions to different issues related to speech technology and speech in industry. Technologies include natural language processing, automatic speech recognition (for under-resourced dialects) and speech synthesis that are useful for applications such as intelligent virtual assistants, among others. Applications cover areas such as sentiment analysis and opinion mining, Arabic named entity recognition, and language modelling. This book is relevant for anyone interested in the latest in language and speech technology.
Book Synopsis Natural Language Processing of Semitic Languages by : Imed Zitouni
Download or read book Natural Language Processing of Semitic Languages written by Imed Zitouni and published by Springer Science & Business. This book was released on 2014-04-22 with total page 477 pages. Available in PDF, EPUB and Kindle. Book excerpt: Research in Natural Language Processing (NLP) has rapidly advanced in recent years, resulting in exciting algorithms for sophisticated processing of text and speech in various languages. Much of this work focuses on English; in this book we address another group of interesting and challenging languages for NLP research: the Semitic languages. The Semitic group of languages includes Arabic (206 million native speakers), Amharic (27 million), Hebrew (7 million), Tigrinya (6.7 million), Syriac (1 million) and Maltese (419 thousand). Semitic languages exhibit unique morphological processes, challenging syntactic constructions and various other phenomena that are less prevalent in other natural languages. These challenges call for unique solutions, many of which are described in this book. The 13 chapters presented in this book bring together leading scientists from several universities and research institutes worldwide. While this book devotes some attention to cutting-edge algorithms and techniques, its primary purpose is a thorough explication of best practices in the field. Furthermore, every chapter describes how the techniques discussed apply to Semitic languages. The book covers both statistical approaches to NLP, which are dominant across various applications nowadays and the more traditional, rule-based approaches, that were proven useful for several other application domains. We hope that this book will provide a "one-stop-shop'' for all the requisite background and practical advice when building NLP applications for Semitic languages.
Book Synopsis Cross Language Information Transfer Between Modern Standard Arabic and Its Dialects by : Tiba Zaki Abdulhameed
Download or read book Cross Language Information Transfer Between Modern Standard Arabic and Its Dialects written by Tiba Zaki Abdulhameed and published by . This book was released on 2020 with total page 86 pages. Available in PDF, EPUB and Kindle. Book excerpt: Significant advances have been made with Modern Standard Arabic (MSA) Automatic Speech Recognition (ASR) applications. Yet, dialectal conversation ASR is still trailing behind due to limited language resources. As is the case in most cultures, the formal Modern Standard Arabic language is not used in daily life. Instead, varieties of regional dialects are spoken, which creates a dire need to address dialect ASR systems. Processing MSA language naturally poses considerable challenges that are passed on to the processing of its derived dialects. In dialects, many words have gradually morphed from MSA pronunciations and at many times have different usages. Also, a significant number of new vocabulary words have been imported from other foreign languages. In addition to these issues, dialects have low resources to be considered for any meaningful natural language processing (NLP) research. Therefore, there is a pressing need for an efficient language model (LM) for deployment in Arabic conversational speech recognition systems. In this thesis, we explore building an Iraqi dialect conversational speech language model based on utilizing MSA data. Because there isn't a pre-defined annotated vocabulary set, our main approach is making use of word embedding for unsupervised clustering of the MSA-Iraqi dialect words. Clustering the dialect words within the relative MSA words is employed to create a class-based LM. This allows the use of MSA data to cover the insufficiency of the dialect data. The model uses the dialect word's statistical history in addition to the statistics of related MSA words to make predictions of the intended spoken word sequence. Thus, efficient word embedding becomes important to produce a reliable LM. To achieve efficient word embedding, first an analysis of the MSA and the Iraqi dialect vocabulary sets and their context intersection is conducted. For this purpose, Dialect Fast Stemming Algorithm (DFSA) is proposed that utilizes the MSA data and a predefined dialect suffixes set. The intersection set enlarged from 42.8% to 54% of the Iraqi vocabulary, and from 8% to 13% of the MSA vocabulary. Second, the syntax and semantic feature vector that is produced by applying the distributional-theory-based word embedding word2vec contained noise from having contexts that appear in MSA or in the dialect solely; thus, applying PCA reduced the perplexity (pp) by 6.7%. Finally, the novel Wasf-Vec topological word embedding algorithm is proposed, which relies on the hypothesis that for a rich morphological language like Arabic, the word’s topological feature is of much significance to be considered. This new feature extraction technique addresses the high morphological properties and reduces PP by 7% when using distributional-theory-based word embedding. Moreover, a deep analysis of the words syntagmatic and paradigmatic relations are illustrated based on solid Arabic and Greek linguistic theories that prove the need of topological word embedding. The three researches compiling this dissertation demonstrate the feasibility of utilizing MSA resources to enhance dialect processing. Further, combining distributional-theory-based and Topology-based word embedding is highly of great intense for future investigation.
Book Synopsis Introduction to Arabic Natural Language Processing by : Nizar Y. Habash
Download or read book Introduction to Arabic Natural Language Processing written by Nizar Y. Habash and published by Springer Nature. This book was released on 2022-06-01 with total page 170 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides system developers and researchers in natural language processing and computational linguistics with the necessary background information for working with the Arabic language. The goal is to introduce Arabic linguistic phenomena and review the state-of-the-art in Arabic processing. The book discusses Arabic script, phonology, orthography, morphology, syntax and semantics, with a final chapter on machine translation issues. The chapter sizes correspond more or less to what is linguistically distinctive about Arabic, with morphology getting the lion's share, followed by Arabic script. No previous knowledge of Arabic is needed. This book is designed for computer scientists and linguists alike. The focus of the book is on Modern Standard Arabic; however, notes on practical issues related to Arabic dialects and languages written in the Arabic script are presented in different chapters. Table of Contents: What is "Arabic"? / Arabic Script / Arabic Phonology and Orthography / Arabic Morphology / Computational Morphology Tasks / Arabic Syntax / A Note on Arabic Semantics / A Note on Arabic and Machine Translation
Book Synopsis Arabic Computational Morphology by : Abdelhadi Soudi
Download or read book Arabic Computational Morphology written by Abdelhadi Soudi and published by Springer Science & Business Media. This book was released on 2007-10-01 with total page 306 pages. Available in PDF, EPUB and Kindle. Book excerpt: This is the first comprehensive overview of computational approaches to Arabic morphology. The subtitle aims to reflect that widely different computational approaches to the Arabic morphological system have been proposed. The book provides a showcase of the most advanced language technologies applied to one of the most vexing problems in linguistics. It covers knowledge-based and empirical-based approaches.
Book Synopsis Handbook of Natural Language Processing and Machine Translation by : Joseph Olive
Download or read book Handbook of Natural Language Processing and Machine Translation written by Joseph Olive and published by Springer Science & Business Media. This book was released on 2011-03-02 with total page 956 pages. Available in PDF, EPUB and Kindle. Book excerpt: This comprehensive handbook, written by leading experts in the field, details the groundbreaking research conducted under the breakthrough GALE program--The Global Autonomous Language Exploitation within the Defense Advanced Research Projects Agency (DARPA), while placing it in the context of previous research in the fields of natural language and signal processing, artificial intelligence and machine translation. The most fundamental contrast between GALE and its predecessor programs was its holistic integration of previously separate or sequential processes. In earlier language research programs, each of the individual processes was performed separately and sequentially: speech recognition, language recognition, transcription, translation, and content summarization. The GALE program employed a distinctly new approach by executing these processes simultaneously. Speech and language recognition algorithms now aid translation and transcription processes and vice versa. This combination of previously distinct processes has produced significant research and performance breakthroughs and has fundamentally changed the natural language processing and machine translation fields. This comprehensive handbook provides an exhaustive exploration into these latest technologies in natural language, speech and signal processing, and machine translation, providing researchers, practitioners and students with an authoritative reference on the topic.
Book Synopsis Proceedings of the International Conference on Natural Language Processing (ICON--2005) by :
Download or read book Proceedings of the International Conference on Natural Language Processing (ICON--2005) written by and published by Allied Publishers. This book was released on 2005 with total page 144 pages. Available in PDF, EPUB and Kindle. Book excerpt: Contributed papers presented at the 2005 International Conference, held at IIT Kanpur, organized by NLP Association of India, etc.
Book Synopsis Applied Arabic Linguistics and Signal & Information Processing by : Raymond Descout
Download or read book Applied Arabic Linguistics and Signal & Information Processing written by Raymond Descout and published by . This book was released on 1987 with total page 264 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis An Arabic Language Resource for Computational Morphology Based on the Semitic Model by : Alexis Neme
Download or read book An Arabic Language Resource for Computational Morphology Based on the Semitic Model written by Alexis Neme and published by . This book was released on 2020 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: We developed an original approach to Arabic traditional morphology, involving new concepts in Semitic lexicology, morphology, and grammar for standard written Arabic. This new methodology for handling the rich and complex Semitic languages is based on good practices in Finite-State technologies (FSA/FST) by using Unitex, a lexicon-based corpus processing suite. For verbs (Neme, 2011), I proposed an inflectional taxonomy that increases the lexicon readability and makes it easier for Arabic speakers and linguists to encode, correct, and update it. Traditional grammar defines inflectional verbal classes by using verbal pattern-classes and root-classes. In our taxonomy, traditional pattern-classes are reused, and root-classes are redefined into a simpler system. The lexicon of verbs covered more than 99% of an evaluation corpus. For nouns and adjectives (Neme, 2013), we went one step further in the adaptation of traditional morphology. First, while this tradition is based on derivational rules, we found our description on inflectional ones. Next, we keep the concepts of root and pattern, which is the backbone of the traditional Semitic model. Still, our breakthrough lies in the reversal of the traditional root-and-pattern Semitic model into a pattern-and-root model, which keeps small and orderly the set of pattern classes and root sub-classes. I elaborated a taxonomy for broken plural containing 160 inflectional classes, which simplifies ten times the encoding of broken plural. Since then, I elaborated comprehensive resources for Arabic. These resources are described in Neme and Paumier (2019). To take into account all aspects of the rich morphology of Arabic, I have completed our taxonomy with suffixal inflexional classes for regular plurals, adverbs, and other parts of speech (POS) to cover all the lexicon. In all, I identified around 1000 Semitic and suffixal inflectional classes implemented with concatenative and non-concatenative FST devices.From scratch, I created 76000 fully vowelized lemmas, and each one is associated with an inflectional class. These lemmas are inflected by using these 1000 FSTs, producing a fully inflected lexicon with more than 6 million forms. I extended this fully inflected resource using agglutination grammars to identify words composed of up to 5 segments, agglutinated around a core inflected verb, noun, adjective, or particle. The agglutination grammars extend the recognition to more than 500 million valid delimited word forms, partially or fully vowelized. The flat file size of 6 million forms is 340 megabytes (UTF-16). It is compressed then into 11 Mbytes before loading to memory for fast retrieval. The generation, compression, and minimization of the full-form lexicon take less than one minute on a common Unix laptop. The lexical coverage rate is more than 99%. The tagger speed is 5000 words/second, and more than 200 000 words/s, if the resources are preloaded/resident in the RAM. The accuracy and speed of our tools result from our systematic linguistic approach and from our choice to embrace the best practices in mathematical and computational methods. The lookup procedure is fast because we use Minimal Acyclic Deterministic Finite Automaton (Revuz, 1992) to compress the full-form dictionary, and because it has only constant strings and no embedded rules. The breakthrough of our linguistic approach remains principally on the reversal of the traditional root-and-pattern Semitic model into a pattern-and-root model.Nonetheless, our computational approach is based on good practices in Finite-State technologies (FSA/FST) as all the full-forms were computed in advance for accurate identification and to get the best from the FSA compression for fast and efficient lookups.
Book Synopsis Novel Techniques for Dialectal Arabic Speech Recognition by :
Download or read book Novel Techniques for Dialectal Arabic Speech Recognition written by and published by Springer. This book was released on 2012-02-11 with total page 134 pages. Available in PDF, EPUB and Kindle. Book excerpt:
