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https://www.um.edu.mt/library/oar/handle/123456789/92556
Title: | An accurate and robust gender identification algorithm |
Authors: | DeMarco, Andrea Cox, Stephen J. |
Keywords: | Natural language processing (Computer science) Automatic speech recognition Language and languages Speech perception Speech processing systems |
Issue Date: | 2011-08 |
Citation: | DeMarco, A., & Cox, S. J. (2011). An accurate and robust gender identification algorithm. In Twelfth Annual Conference of the International Speech Communication Association. |
Abstract: | We describe a robust, unsupervised method of automatic gender identification from speech. We first design a baseline gender classifier based on MFCC features, and add a second classifier that uses context-dependent but text-independent pitch features. The results of these classifiers are then examined for disagree- ments in gender classification. Any disagreements are resolved by the use of a novel pitch-shifting mechanism applied to the ut- terances. We show how the acoustic context classifier provides very good gender identification results, and how these are fur- ther enhanced by the pitch-shifting process. Furthermore this enhancement is preserved across a set of different corpora. |
URI: | https://www.um.edu.mt/library/oar/handle/123456789/92556 |
ISBN: | 9781618392701 |
Appears in Collections: | Scholarly Works - InsSSA |
Files in This Item:
File | Description | Size | Format | |
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An_Accurate_and_Robust_Gender_Identification_Algorithm(2011).pdf Restricted Access | 210.15 kB | Adobe PDF | View/Open Request a copy |
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