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Description
Title: | Example-based audio editing |
Author(s): | Anushiravani, Ramin |
Advisor(s): | Smaragdis, Paris |
Department / Program: | Electrical & Computer Eng |
Discipline: | Electrical and Computer Engineering |
Degree Granting Institution: | University of Illinois at Urbana-Champaign |
Degree: | M.S. |
Genre: | Thesis |
Subject(s): | signal processing
speech enhancement audio processing audio editor denoising dereverberation equalization acoustic matching digital audio work station example-based editing machine learning |
Abstract: | Traditionally, audio recordings are edited through digital audio workstations (DAWs), which give users access to different tools and parameters through a graphical user interface (GUI) without prior knowledge in coding or signal processing. The complexity of working with DAWs and the undeniable need for strong listening skills have made audio editing unpopular among novice users and time consuming for professionals. We propose an intelligent audio editor (EBAE) that automates major audio editing routines with the use of an example sound and efficiently provides users with high-quality results. EBAE first extracts meaningful information from an example sound that already contains the desired effects and then applies them to a desired recording by employing signal processing and machine learning techniques. |
Issue Date: | 2016-11-21 |
Type: | Text |
URI: | http://hdl.handle.net/2142/95331 |
Rights Information: | Copyright 2016 Ramin Anushiravani |
Date Available in IDEALS: | 2017-03-01 |
Date Deposited: | 2016-12 |
This item appears in the following Collection(s)
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Dissertations and Theses - Electrical and Computer Engineering
Dissertations and Theses in Electrical and Computer Engineering -
Graduate Dissertations and Theses at Illinois
Graduate Theses and Dissertations at Illinois