Dialect Accent Features for Establishing Speaker Identity [electronic resource] : A Case Study / by Manisha Kulshreshtha, Ramkumar Mathur.

By:

Kulshreshtha, Manisha [author.]

Contributor(s):

Material type: Text

TextSeries: SpringerBriefs in Electrical and Computer EngineeringPublisher: Boston, MA : Springer US, 2012Description: XII, 60 p. online resourceContent type:

text

Media type:

computer

Carrier type:

online resource

ISBN:

9781461411383

Subject(s):

Additional physical formats: Printed edition:: No titleDDC classification:

621.382 23

LOC classification:

TK5102.9
TA1637-1638
TK7882.S65

Online resources:

Click here to access online

Contents:

1. Introduction -- 2. Hindi Language and Its Dialects -- 3. Speech Materials and Instrumentation -- 4. Analysis and Results -- 5. Conclusion.

In: Springer eBooksSummary: 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.

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Holdings
Item type	Current library	Call number	Status	Date due	Barcode
E-Book	Central Library		Available		E-39710

1. Introduction -- 2. Hindi Language and Its Dialects -- 3. Speech Materials and Instrumentation -- 4. Analysis and Results -- 5. Conclusion.

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.

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