Year: 2013
Type: preprint
Abstract: Speech is a natural form of communication for human beings, and computers with the ability to understand speech and speak with a human voice are expected to contribute to the development of more natural man-machine interfaces. Computers with this kind of ability are gradually becoming a reality, through the evolution of speech recognition technologies. Speech is being an important mode of interaction with computers. In this paper Feature extraction is implemented using well-known Mel-Frequency Cepstral Coefficients (MFCC).Pattern matching is done using Dynamic time warping (DTW) algorithm.
Source: arXiv (Cornell University)
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W1602767455