Determination of Extent of Similarity between Mimic and Genuine Voice Signals Using MFCC Features
Sunil N. Nikhate, Archana Kedar Chaudhari, Jayant V Kulkarni · 2019 3rd International conference on Electronics, Communication and Aerospace Technology (ICECA) · 2019
Human voice plays a very principle role in effective communication among human beings. Since, every human has an unique characteristics (features) of his voice, and speech processing is the field of engineering which performs various operations on speech & extract those characteristics. These characteristics or features are unique for specific person. Human ears are not able to identify such features at micro level. This paper presents approach to extract features from original and dubbing audio signals and analysis with the help frame segmentation analysis approach & Mel Frequency Cepstral Coefficient (MFCC) feature extraction algorithm.