Cognitively Inspired Feature Extraction and Speech Recognition for Automated Hearing Loss Testing

A bio-inspired feature extraction for robust speech recognition

In this paper, a feature extraction method for robust speech recognition in noisy environments is proposed. The proposed method is motivated by a biologically inspired auditory model which simulates the outer/middle ear filtering by a low-pass filter and the spectral behaviour of the cochlea by the Gammachirp auditory filterbank (GcFB). The speech recognition performance of our method is tested...

Physiologically-inspired feature extraction for emotion recognition

In this paper, we proposed a new feature extraction method for emotion recognition based on the knowledge of the emotion production mechanism in physiology. It was reported by physiacoustist that emotional speech is differently encoded from the normal speech in terms of articulation organs and that emotion information in speech is concentrated in different frequencies caused by the different mo...

Automated Feature Extraction for Object Recognition

Automated image interpretation is an important task in numerous applications ranging from security systems to natural resource inventorization based on remote-sensing. Recently, a second generation of adaptive machine-learned image interpretation systems have shown expert-level performance in several challenging domains. While demonstrating an unprecedented improvement over hand-engineered and ...

Feature Extraction Techniques for Speech Recognition

Speech Recognition as Feature Extraction for Speaker Recognition

Information from speech recognition can be used in various ways in state-of-the-art speaker recognition systems. This includes the obvious use of recognized words to enable the use of text-dependent speaker modeling techniques when the words spoken are not given. Furthermore, it has been shown that the choice of words and phones itself can be a useful indicator of speaker identity. Also, recogn...