Bangla Speech Emotion Detection using Machine Learning Ensemble Methods

Fault Detection of Anti-friction Bearing using Ensemble Machine Learning Methods

Anti-Friction Bearing (AFB) is a very important machine component and its unscheduled failure leads to cause of malfunction in wide range of rotating machinery which results in unexpected downtime and economic loss. In this paper, ensemble machine learning techniques are demonstrated for the detection of different AFB faults. Initially, statistical features were extracted from temporal vibratio...

Speech Emotion Classification using Machine Learning

In recent years, the interaction between humans and machines has become an issue of concern. This paper results from study of various researches related to the investigation of the six basic human emotions which include anger, dislike, fear, happiness, sadness and surprise. [1, 3] Feature extraction is done from various voice utterances recorded from different persons. The various features like...

Ensemble machine learning methods for acoustic modeling of speech

Machine Learning Methods in the Application of Speech Emotion Recognition

Machine Learning concerns the development of algorithms, which allows machine to learn via inductive inference based on observation data that represent incomplete information about statistical phenomenon. Classification, also referred to as pattern recognition, is an important task in Machine Learning, by which machines “learn” to automatically recognize complex patterns, to distinguish between...

Ensemble Methods in Machine Learning

Ensemble methods are learning algorithms that construct a set of classi ers and then classify new data points by taking a weighted vote of their predictions The original ensemble method is Bayesian aver aging but more recent algorithms include error correcting output coding Bagging and boosting This paper reviews these methods and explains why ensembles can often perform better than any single ...