Authors:
- Combines basic conceptual theory, case studies and Hindi Phonology
- Covers the basic concept of accent features in which there are very few published case studies of empirical work
- Contains several figures and tables to help readers understand the science of accent features extraction
Part of the book series: SpringerBriefs in Speech Technology (BRIEFSSPEECHTECH)
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Table of contents (5 chapters)
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Front Matter
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Back Matter
About this book
Dialect Accent Features for Establishing Speaker Identity: A Case Study discusses the subject of forensic voice identification and speaker profiling. Specifically focusing on speaker profiling and using dialects of the Hindi language, widely used in India, the authors have contributed to the body of research on speaker identification by using accent feature as the discriminating factor.
This case study contributes to the understanding of the speaker identification process in a situation where unknown speech samples are in different language/dialect than the recording of a suspect. The authors' data establishes that vowel quality, quantity, intonation and tone of a speaker as compared to Khariboli (standard Hindi) could be the potential features for identification of dialect accent.
Authors and Affiliations
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Yale University, Haskins Laboratories, Bronx, USA
Manisha Kulshreshtha
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, Dept. of Microbiology and Immunology, Columbia University Medical Center, New York, USA
Ramkumar Mathur
Bibliographic Information
Book Title: Dialect Accent Features for Establishing Speaker Identity
Book Subtitle: A Case Study
Authors: Manisha Kulshreshtha, Ramkumar Mathur
Series Title: SpringerBriefs in Speech Technology
DOI: https://doi.org/10.1007/978-1-4614-1138-3
Publisher: Springer New York, NY
eBook Packages: Engineering, Engineering (R0)
Copyright Information: Manisha Kulshreshtha 2012
Hardcover ISBN: 978-1-4614-1137-6Published: 24 March 2012
Softcover ISBN: 978-1-4899-9939-9Published: 13 April 2014
eBook ISBN: 978-1-4614-1138-3Published: 24 March 2012
Series ISSN: 2191-737X
Series E-ISSN: 2191-7388
Edition Number: 1
Number of Pages: XII, 60
Topics: Signal, Image and Speech Processing, Natural Language Processing (NLP), Pattern Recognition