Kamaruddin, Norhaslinda and Abdul Rahman, Abdul Wahab (2009) CMAC for speech emotion profiling. In: Proceedimgs of the Interspeech 2009 10th Annual Conference of the International Speech Communication Association, 6 - 10 September 2010, Brighton, United Kingdom.
PDF (CMAC for speech emotion profiling)
Restricted to Registered users only Download (362kB) | Request a copy |
Abstract
Cultural differences have been one of the many factors that can cause failures in speech emotion analysis. If this cultural parameter could be regarded as noise artifacts in detecting emotion in speech, we could then extract pure emotion speech signal from the raw emotional speech. In this paper we use the amplitude spectral subtraction (ASS) method to profile the emotion from raw emotional speech based on the affection space model. In addition, the robustness of the cerebellar model arithmetic computer (CMAC) is used to ensure that all other noise artifacts can be suppressed. Result from the speech emotion profiling shows potential of such technique to visualize hidden features for detecting intra-cultural and inter-cultural variation that is missing from current approach of speech emotion recognition
Item Type: | Conference or Workshop Item (UNSPECIFIED) |
---|---|
Additional Information: | 6145/10075 |
Uncontrolled Keywords: | Affection space model, emotion profiling, amplitude spectral subtraction (ASS), intra-cultural and intercultural assessment, cerebellar model arithmetic computer(CMAC) |
Subjects: | T Technology > T Technology (General) T Technology > T Technology (General) > T10.5 Communication of technical information |
Kulliyyahs/Centres/Divisions/Institutes (Can select more than one option. Press CONTROL button): | Kulliyyah of Information and Communication Technology Kulliyyah of Information and Communication Technology |
Depositing User: | Prof Abdul Wahab Abdul Rahman |
Date Deposited: | 19 Mar 2012 09:26 |
Last Modified: | 16 Dec 2020 23:25 |
URI: | http://irep.iium.edu.my/id/eprint/10075 |
Actions (login required)
View Item |