AES E-Library

AES E-Library

Voiced/Unvoiced/Silence Classification of Noisy Speech in Real Time Audio Signal Processing

The classification of noisy speech signal into voiced, unvoiced, and silence provides a preliminary acoustic segmentation for audio signal processing applications, such as digital coding, speech enhancement, and identification. The proposed technique employs a two-staged structure and uses the normalized segmental energy, normalized partial sum of autocorrelation coefficients, and spectral envelope pattern matching as the measurement criteria to classify the voiced and unvoiced speech segments from background noise. The reference noise pattern is updated by incoming silent segments and the classifier can work in real time. Simulation results have shown that this technique is robust even if the audio signal is corrupted by heavy broadband noise.

AES Convention: Paper Number:
Publication Date:

Click to purchase paper as a non-member or login as an AES member. If your company or school subscribes to the E-Library then switch to the institutional version. If you are not an AES member and would like to subscribe to the E-Library then Join the AES!

This paper costs $33 for non-members and is free for AES members and E-Library subscribers.

Learn more about the AES E-Library

E-Library Location:

Start a discussion about this paper!

AES - Audio Engineering Society