Sound effects and sound visualization in Artikulate: Difference between revisions
(Created page with "==Sound effects and visualization== Artikulate is an application which focuses upon improving the users' pronunciation skills by repeating native speaker recordings, recordin...") |
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So we would like to have a filter implemented within Artikulate and also a way of visually representing how two recorded audio waves differ. | So we would like to have a filter implemented within Artikulate and also a way of visually representing how two recorded audio waves differ. | ||
==Noise removal== | |||
In the context of noise removal we need to get a profile of background noise before we can go on with filtering. We may easily implement it in the application interface by telling the user to wait for a couple of seconds after he/she presses the record button. Then we will be getting a noise profile of the background noise from the first couple of seconds in the audio. | |||
Noise removal is one of the most widely researched field of computer science. There are numerous works in the context of cleaning background noise from speech signals alone. Following is a very brief abstract of such two algorithms. | |||
===Suppression of noise using spectral subtraction=== | |||
Revision as of 07:49, 23 February 2014
Sound effects and visualization
Artikulate is an application which focuses upon improving the users' pronunciation skills by repeating native speaker recordings, recording that try and comparing both. By repeating these trials, a learner can continuously improve his/her language skills. But when a user records his/her own voice through a microphone invariably there are noises in the recorded audio and it becomes harder to analyze how well the user is faring.
So we would like to have a filter implemented within Artikulate and also a way of visually representing how two recorded audio waves differ.
Noise removal
In the context of noise removal we need to get a profile of background noise before we can go on with filtering. We may easily implement it in the application interface by telling the user to wait for a couple of seconds after he/she presses the record button. Then we will be getting a noise profile of the background noise from the first couple of seconds in the audio.
Noise removal is one of the most widely researched field of computer science. There are numerous works in the context of cleaning background noise from speech signals alone. Following is a very brief abstract of such two algorithms.