Sub-word based Tigrinya speech recognizer. An experiment using hidden Markov model PDF Download
Are you looking for read ebook online? Search for your book and save it on your Kindle device, PC, phones or tablets. Download Sub-word based Tigrinya speech recognizer. An experiment using hidden Markov model PDF full book. Access full book title Sub-word based Tigrinya speech recognizer. An experiment using hidden Markov model by Temesgen Gebretsadik. Download full books in PDF and EPUB format.
Author: Temesgen Gebretsadik Publisher: GRIN Verlag ISBN: 3346090310 Category : Computers Languages : en Pages : 133
Book Description
Master's Thesis from the year 2013 in the subject Computer Science - Miscellaneous, grade: Very good, , course: Masters of Science in Computer Science, language: English, abstract: Speech recognition, a process of changing speech to text, has been one of a research area for the last many decades. Even though there are several techniques of modeling a speech recognizer, yet it is still challenging to find one that overcomes all the limitations. So this thesis examines the possibility of developing Tigrinya language speech recognizer by finding out which sub-word unit is most appropriate in developing efficient large vocabulary, speaker independent, and continuous Tigrinya speech recognition system using hidden Markov models (HMM). The recognizer was developed using Hidden Markov Model, and the Hidden Markov Modeling Toolkit was used to implement it. In the course of developing this system, the speech data is recorded at a sampling rate of 16 KHz and the recorded speech is converted into Mel Frequency Cepstral Coefficient (MFCC) vectors for further analysis and processing. In this research work, 1000 selected utterances were uttered by 26 selected peoples from different age group and sex constituting of 4643 unique words. Accordingly, the database is set up into two ways the first database comprised of 1000 utterances that are used for training and out of which 100 sentences were taken for testing and evaluation whereas the second database consists of 900 utterances for training and 100 utterances for test and evaluation which is different from the training set. Furthermore, the data is preprocessed in line with the requirements of the HTK toolkit and both the text and speech corpuses were prepared in consultation with the domain experts.
Author: Temesgen Gebretsadik Publisher: GRIN Verlag ISBN: 3346090310 Category : Computers Languages : en Pages : 133
Book Description
Master's Thesis from the year 2013 in the subject Computer Science - Miscellaneous, grade: Very good, , course: Masters of Science in Computer Science, language: English, abstract: Speech recognition, a process of changing speech to text, has been one of a research area for the last many decades. Even though there are several techniques of modeling a speech recognizer, yet it is still challenging to find one that overcomes all the limitations. So this thesis examines the possibility of developing Tigrinya language speech recognizer by finding out which sub-word unit is most appropriate in developing efficient large vocabulary, speaker independent, and continuous Tigrinya speech recognition system using hidden Markov models (HMM). The recognizer was developed using Hidden Markov Model, and the Hidden Markov Modeling Toolkit was used to implement it. In the course of developing this system, the speech data is recorded at a sampling rate of 16 KHz and the recorded speech is converted into Mel Frequency Cepstral Coefficient (MFCC) vectors for further analysis and processing. In this research work, 1000 selected utterances were uttered by 26 selected peoples from different age group and sex constituting of 4643 unique words. Accordingly, the database is set up into two ways the first database comprised of 1000 utterances that are used for training and out of which 100 sentences were taken for testing and evaluation whereas the second database consists of 900 utterances for training and 100 utterances for test and evaluation which is different from the training set. Furthermore, the data is preprocessed in line with the requirements of the HTK toolkit and both the text and speech corpuses were prepared in consultation with the domain experts.
Author: Siegbert Uhlig Publisher: Otto Harrassowitz Verlag ISBN: 9783447047999 Category : History Languages : en Pages : 1140
Book Description
The XVth International Conference of Ethiopian Studies took place in Hamburg in July 2003. More than 400 scientists from over 25 countries participated. 130 contributions from the program were selected for this volume. They are mostly written in English and deal on the regions of Ethiopia and Eritrea and cover the span from the 4th Century to the present. The volume is divided into the following chapters: Anthropology (20 Articles), History (25), Arts (10), Literature and Philology (10), Religion (5), Languages and Linguistics (25), Law and Politics (10), Environmental, Economic and Educational Issues (10).
Author: Soumya Sen Publisher: Springer ISBN: 9811360987 Category : Technology & Engineering Languages : en Pages : 107
Book Description
This book offers an overview of audio processing, including the latest advances in the methodologies used in audio processing and speech recognition. First, it discusses the importance of audio indexing and classical information retrieval problem and presents two major indexing techniques, namely Large Vocabulary Continuous Speech Recognition (LVCSR) and Phonetic Search. It then offers brief insights into the human speech production system and its modeling, which are required to produce artificial speech. It also discusses various components of an automatic speech recognition (ASR) system. Describing the chronological developments in ASR systems, and briefly examining the statistical models used in ASR as well as the related mathematical deductions, the book summarizes a number of state-of-the-art classification techniques and their application in audio/speech classification. By providing insights into various aspects of audio/speech processing and speech recognition, this book appeals a wide audience, from researchers and postgraduate students to those new to the field.
Author: Uday Kamath Publisher: Springer ISBN: 3030145964 Category : Computers Languages : en Pages : 640
Book Description
This textbook explains Deep Learning Architecture, with applications to various NLP Tasks, including Document Classification, Machine Translation, Language Modeling, and Speech Recognition. With the widespread adoption of deep learning, natural language processing (NLP),and speech applications in many areas (including Finance, Healthcare, and Government) there is a growing need for one comprehensive resource that maps deep learning techniques to NLP and speech and provides insights into using the tools and libraries for real-world applications. Deep Learning for NLP and Speech Recognition explains recent deep learning methods applicable to NLP and speech, provides state-of-the-art approaches, and offers real-world case studies with code to provide hands-on experience. Many books focus on deep learning theory or deep learning for NLP-specific tasks while others are cookbooks for tools and libraries, but the constant flux of new algorithms, tools, frameworks, and libraries in a rapidly evolving landscape means that there are few available texts that offer the material in this book. The book is organized into three parts, aligning to different groups of readers and their expertise. The three parts are: Machine Learning, NLP, and Speech Introduction The first part has three chapters that introduce readers to the fields of NLP, speech recognition, deep learning and machine learning with basic theory and hands-on case studies using Python-based tools and libraries. Deep Learning Basics The five chapters in the second part introduce deep learning and various topics that are crucial for speech and text processing, including word embeddings, convolutional neural networks, recurrent neural networks and speech recognition basics. Theory, practical tips, state-of-the-art methods, experimentations and analysis in using the methods discussed in theory on real-world tasks. Advanced Deep Learning Techniques for Text and Speech The third part has five chapters that discuss the latest and cutting-edge research in the areas of deep learning that intersect with NLP and speech. Topics including attention mechanisms, memory augmented networks, transfer learning, multi-task learning, domain adaptation, reinforcement learning, and end-to-end deep learning for speech recognition are covered using case studies.
Author: Jeff Mielke Publisher: Oxford Studies in Typology and ISBN: Category : Language Arts & Disciplines Languages : en Pages : 308
Book Description
This book makes a fundamental contribution to phonology, linguistic typology, and the nature of the human language faculty. Distinctive features in phonology distinguish one meaningful sound from another. Since the mid-twentieth century they have been seen as a set characterizing all possible phonological distinctions and as an integral part of Universal Grammar, the innate language faculty underlying successive versions of Chomskyan generative theory. The usefulness of distinctive features in phonological analysis is uncontroversial, but the supposition that features are innate and universal rather than learned and language-specific has never, until now, been systematically tested. In his pioneering account Jeff Mielke presents the results of a crosslinguistic survey of natural classes of distinctive features covering almost six hundred of the world's languages drawn from a variety of different families. He shows that no theory is able to characterize more than 71 percent of classes, and further that current theories, deployed either singly or collectively, do not predict the range of classes that occur and recur. He reveals the existence of apparently unnatural classes in many languages. Even without these findings, he argues, there are reasons to doubt whether distinctive features are innate: for example, distinctive features used in signed languages are different from those in spoken languages, even though deafness is generally not hereditary. The author explains the grouping of sounds into classes and concludes by offering a unified account of what previously have been considered to be natural and unnatural classes. The data on which the analysis is based are freely available in a program downloadable from the publisher's web site.
Author: Fisseha Mekuria Publisher: Springer ISBN: 3030266303 Category : Computers Languages : en Pages : 368
Book Description
This book constitutes the proceedings of the Second International Conference on Information and Communication Technology for Development for Africa, ICT4DA 2019, held in Bahir Dar, Ethiopia, in May 2019. The 29 revised full papers presented were carefully reviewed and selected from 69 submissions. The papers address the impact of ICT in fostering economic development in Africa. In detail they cover the following topics: artificial intelligence and data science; wireless and mobile computing; and Natural Language Processing.
Author: Mulatu Liyew Berihun Publisher: Springer Nature ISBN: 3030937127 Category : Computers Languages : en Pages : 600
Book Description
This two-volume set of LNICST 411 and 412 constitutes the refereed post-conference proceedings of the 9th International Conference on Advancement of Science and Technology, ICAST 2021, which took place in August 2021. Due to COVID-19 pandemic the conference was held virtually. The 80 revised full papers were carefully reviewed and selected from 202 submissions. The papers present economic and technologic developments in modern societies in 7 tracks: Chemical, Food and Bioprocess Engineering; Electrical and Electronics Engineering; ICT, Software and Hardware Engineering; Civil, Water Resources, and Environmental Engineering ICT; Mechanical and Industrial Engineering; Material Science and Engineering; Energy Science, Engineering and Policy.
Author: Judith Aissen Publisher: Taylor & Francis ISBN: 1351754807 Category : Foreign Language Study Languages : en Pages : 790
Book Description
The Mayan Languages presents a comprehensive survey of the language family associated with the Classic Mayan civilization (AD 200–900), a family whose individual languages are still spoken today by at least six million indigenous Maya in Mexico, Guatemala, Belize, and Honduras. This unique resource is an ideal reference for advanced undergraduate and postgraduate students of Mayan languages and linguistics. Written by a team of experts in the field, The Mayan Languages presents in-depth accounts of the linguistic features that characterize the thirty-one languages of the family, their historical evolution, and the social context in which they are spoken. The Mayan Languages: provides detailed grammatical sketches of approximately a third of the Mayan languages, representing most of the branches of the family; includes a section on the historical development of the family, as well as an entirely new sketch of the grammar of "Classic Maya" as represented in the hieroglyphic script; provides detailed state-of-the-art discussions of the principal advances in grammatical analysis of Mayan languages; includes ample discussion of the use of the languages in social, conversational, and poetic contexts. Consisting of topical chapters on the history, sociolinguistics, phonology, morphology, syntax, semantics, discourse structure, and acquisition of the Mayan languages, this book will be a resource for researchers and other readers with an interest in historical linguistics, linguistic anthropology, language acquisition, and linguistic typology.
Author: Saso Dzeroski Publisher: Springer ISBN: 9783540661092 Category : Computers Languages : en Pages : 312
Book Description
This book constitutes the refereed proceedings of the 9th International Conference on Inductive Logic Programming, ILP-99, held in Bled, Slovenia, in June 1999. The 24 revised papers presented were carefully reviewed and selected from 40 submissions. Also included are abstracts of three invited contributions. The papers address all current issues in inductive logic programming and inductive learning, from foundational and methodological issues to applications, e.g. in natural language processing, knowledge discovery, and data mining.
Author: Temesgen Gebretsadik
Author: Temesgen Gebretsadik
Author: Siegbert Uhlig
Author: Soumya Sen
Author: Uday Kamath
Author: 
Author: Jeff Mielke
Author: Fisseha Mekuria
Author: Mulatu Liyew Berihun
Author: Judith Aissen
Author: Saso Dzeroski