The algorithm employs a method of expanded spectral subtraction based on the noise compensation structure, which can estimate the noise during speech presence.

Speech endpoint detection algorithm with low signal-to-noise based on improved conventional spectral entropy. Abstract: Endpoint detection is a typical ...

The paper pointes out an endpoint detection algorithm combining two methods together: the one is improved spectral subtraction based on multitaper spectral ...

Abstract: A novel speech endpoint detection algorithm was proposed to improve the accuracy in low signal-to-noise ratio (SNR) conditions.

Computer Science. 2010. TLDR. The method improves the discriminability between speech and noise, and the speech detection ratio is increased with lower SNR ...

Jan 11, 2024 · In the problem of low SNR, this paper proposes an improved endpoint detection algorithm ... signal-to-noise ratios greater than 30 dB). However, ...

ABSTRACT. It is found that the detection using basic spectral entropy becomes difficult and inaccurate when speech signals are contaminated by high noise.

Therefore, this paper proposes a speech endpoint detection algorithm for low SNR. In this paper, Savitzky-Golay filtering, improved sub-band energy entropy and ...

The robustness and detection accuracy of algorithms have always been hot topics for many scholars in the condition of low Signal-to-Noise Ratio (SNR) and ...

This paper proposes an improved endpoint detection algorithm based on improved spectral subtraction with multi-taper spectrum and energy-zero ratio that has ...