Speech is the natural mode of communication between humans. Human-to-machine interaction is gaining importance in the past few decades which demands the machine to be able to analyze, respond and perform tasks at the same speed as performed by human. This task is achieved by Automatic Speech Recognition (ASR) system which is typically a speech-to-text converter. In order to recognize the areas of further research in ASR, one must be aware of the current approaches, challenges faced by each and issues that needs to be addressed. Therefore, in this paper human speech production mechanism is discussed. The various speech recognition techniques and models are addressed in detail. The performance parameters that measure the accuracy of the system in recognizing the speech signal are described.

No abstract

No abstract

In recent years biometric identification of persons has gained major importance in the world from its applications, such as border security, access control and forensic. Iris recognition is one of the most booming biometric modalities. Due to its unique character as a biometric feature, iris identification and verification systems have become one of the most accurate biometric modality. In this paper, the different steps to recognize an iris image which includes acquisition, segmentation, normalization, feature extraction and matching are discussed. The performance of the iris recognition system depends on segmentation and normalization techniques adopted before extracting the iris features. It also provides an extensive review of the significant methods of iris recognition systems. In addition to this, the challenges and achievements of the iris are presented.