Mr. Phobia J. Setubal Profile

Phobia J. Setubal

at Univ Federal de Santa Cararina

SPIE Involvement:

Author

Publications (1)

This will count as one of your downloads.

You will have access to both the presentation and article (if available).

DOWNLOAD NOW

This content is available for download via your institution's subscription. To access this item, please sign in to your personal account.

Email or Username Forgot your username?

Password Forgot your password?

Show

Keep me signed in

No SPIE account? Create an account

Proceedings Article | 25 October 2004 Paper

Segmentation of singing voice within music signals

Phabio Setubal, Sidnei Filho, Rui Seara

Proceedings Volume 5601, (2004) https://doi.org/10.1117/12.571280

KEYWORDS: Databases, Signal processing, Error analysis, Autoregressive models, Feature extraction, Smoothing, Shape analysis, Automatic tracking, Image classification, Internet

Read Abstract +

This paper proposes a novel approach to accomplish the automatic segmentation of singing voice within music signals, based on the difference between the dynamic harmonic content of singing voice and that of musical instrument signals. The obtained results are compared with those of another approach proposed in the literature, considering the same music database. For both techniques, an accuracy rate around 80% is obtained, even using a more rigorous performance measure for our approach only. As an advantage, the new procedure presents lower computational complexity. In addition, we discuss other results obtained by extending the tests over the whole database (upholding the same performance level) and by discriminating the error types (boundaries shifted in time, insertion and deletion of singing segments). The analysis of these errors suggests some alternative ways of reducing them, as for example, to adopt a confidence level based on a minimum harmonic content for the input signals. In this way, considering only signals with confidence level equal to one, the obtained performance is improved to almost 87%.

My Library

You currently do not have any folders to save your paper to! Create a new folder below.

Folder Name

Folder Description

View contact details

UPDATE YOUR PROFILE

Is this your profile? Update it now.

Sign into your SPIE.org account

Don’t have a profile and want one?

Create an account on SPIE.org

Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks. You are receiving this notice because your organization may not have SPIE eBooks access.*

*Shibboleth/Open Athens users─please sign in to access your institution's subscriptions.

To obtain this item, you may purchase the complete book in print or electronic format on SPIE.org.

ORGANIZATIONAL
Sign in with credentials provided by your organization.

Organizational Username

Organizational Password

Show/Hide Password

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available

Members:

Non-members: ADD TO CART

Keywords/Phrases

Search In:

Publication Years