published: Aug. 5, 2010, recorded: July 2010, views: 9117
Report a problem or upload filesIf you have found a problem with this lecture or would like to send us extra material, articles, exercises, etc., please use our ticket system to describe your request and upload the data.
Enter your e-mail into the 'Cc' field, and we will keep you updated with your request's status.
The lecture presents various aspects of automatic speech processing (SP), from spoken contents extraction to high level categorization of speech signals. We show how machine learning provides solutions to the main issues that the speech processing systems have to deal with. Speech is one of the main way that humans communicate together. It is a complex process that involves, in a highly integrated way, perception abilities and cognitive processes. In spite of the efforts produced by the scientific community for simulating these abilities, knowledge-based approaches failed in modeling of speech. Nowadays, most of the SP methods relies on statistical modeling of speech. The lecture presents this theorical framework in which the major issues in speech processing are formulated. Then, the main tasks of SP are overviewed, especially speaker identification and speech recognition and understanding.
Link this pageWould you like to put a link to this lecture on your homepage?
Go ahead! Copy the HTML snippet !