Comparison of speaker recognition methods using statistical features and dynamic features

Vehicle Logo Recognition Using Image Matching and Textural Features

In recent years, automatic recognition of vehicle logos has become one of the important issues in modern cities. This is due to the unlimited increase of cars and transportation systems that make it impossible to be fully managed and monitored by human. In this research, an automatic real-time logo recognition system for moving cars is introduced based on histogram manipulation. In the proposed...

Bottleneck features for speaker recognition

Bottleneck neural networks have recently found success in a variety of speech recognition tasks. This paper presents an approach in which they are utilized in the front-end of a speaker recognition system. The network inputs are melfrequency cepstral coefficients (MFCCs) from multiple consecutive frames and the outputs are speaker labels. We propose using a recording-level criterion that is opt...

Speaker Recognition Usi Features Sele

A new method of text-independent speaker recognition using discriminative feature selection is proposed in this paper. The method is compared with the classical UBM-GMM and hybrid codebook approaches. The characteristics of the proposed method are as follows: feature parameters extraction, vector quantization with the growing neural gas (GNG) algorithm and discriminative feature selection (DFS)...

Face Recognition Using Different Statistical Features

Speaker Features And Recognition Techniques : A Review

This paper gives an overview of various methods and techniques used for feature extraction and modeling in speaker recognition. The research in speaker recognition have been evolved starting from short time features reflecting spectral properties of speech (low-level or physical traits) to the high level features (behavioural traits) such as prosody, phonetic information, conversational pattern...