Maximum Entropy-based Emotion Recognition Model using Individual Average Difference
نویسندگان
چکیده
منابع مشابه
A Predictive Model for Emotion Recognition Based on Individual Characteristics and Autonomic Changes
Introduction: The importance of individual differences in the problem of emotion recognition has been repeatedly stated in the studies. The major concentration of this study was the prediction of heart rate variability (HRV) changes due to affective stimuli from the subject characteristics. These features were age (A), gender (G), linguality (L), and sleep (S) information. In addition, the most...
متن کاملName Origin Recognition Using Maximum Entropy Model and Diverse Features
Name origin recognition is to identify the source language of a personal or location name. Some early work used either rulebased or statistical methods with single knowledge source. In this paper, we cast the name origin recognition as a multi-class classification problem and approach the problem using Maximum Entropy method. In doing so, we investigate the use of different features, including ...
متن کاملSpeech recognition error correction using maximum entropy language model
A speech interface is often required in many application environments, such as telephone-based information retrieval, car navigation systems, and user-friendly interfaces, but the low speech recognition rate makes it difficult to extend its application to new fields. We propose a domain adaptation technique via error correction with a maximum entropy language model, which is a general and elega...
متن کاملHMM-Based Emotional Speech Synthesis Using Average Emotion Model
This paper presents a technique for synthesizing emotional speech based on an emotion-independent model which is called “average emotion” model. The average emotion model is trained using a multi-emotion speech database. Applying a MLLR-based model adaptation method, we can transform the average emotion model to present the target emotion which is not included in the training data. A multi-emot...
متن کاملSpeech Emotion Recognition Using Scalogram Based Deep Structure
Speech Emotion Recognition (SER) is an important part of speech-based Human-Computer Interface (HCI) applications. Previous SER methods rely on the extraction of features and training an appropriate classifier. However, most of those features can be affected by emotionally irrelevant factors such as gender, speaking styles and environment. Here, an SER method has been proposed based on a concat...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: The Journal of the Korean Institute of Information and Communication Engineering
سال: 2010
ISSN: 2234-4772
DOI: 10.6109/jkiice.2010.14.7.1557