Effect of High-Energy Voiced Speech Segments and Speaker Gender on Shouted Speech Detection

2021 ◽  
Author(s):  
Shikha Baghel ◽  
S. R. M. Prasanna ◽  
Prithwijit Guha
Keyword(s):  
High Energy ◽  
Speech Detection ◽  
Voiced Speech ◽  
Speech Segments

Variable Ratio Sample Rate Conversion Based on Fractional Delay Filter

2015 ◽  
Vol 39 (2) ◽  
pp. 231-242 ◽  
Author(s):  
Marek Blok ◽  
Piotr Drózda
Keyword(s):  
Speech Signal Processing ◽  
Farrow Structure ◽  
Conversion Algorithm ◽  
Window Method ◽  
Voiced Speech ◽  
Fractional Delay ◽  
Sample Rate ◽  
Fractional Delay Filter ◽  
Speech Segments ◽  
Rate Conversion

Abstract In this paper a sample rate conversion algorithm which allows for continuously changing resampling ratio has been presented. The proposed implementation is based on a variable fractional delay filter which is implemented by means of a Farrow structure. Coefficients of this structure are computed on the basis of fractional delay filters which are designed using the offset window method. The proposed approach allows us to freely change the instantaneous resampling ratio during processing. Using such an algorithm we can simulate recording of audio on magnetic tape with nonuniform velocity as well as remove such distortions. We have demonstrated capabilities of the proposed approach based on the example of speech signal processing with a resampling ratio which was computed on the basis of estimated fundamental frequency of voiced speech segments.

Detection of Voiced Speech Segments of Esophageal Speakers

2006 ◽  
Vol 65 (7) ◽  
pp. 655-665
Author(s):  
A. Mantilla-Caeiros ◽  
Hector Manuel Perez-Meana ◽  
D. Mata-Verde ◽  
C. Angeles-Pina ◽  
J. Alvarado-Soriano ◽  
...  
Keyword(s):  
Voiced Speech ◽  
Speech Segments

scholarly journals Application of Poincare-Mapping of Voiced-Speech Segments for Emotion Sensing

Sensors ◽  
2009 ◽  
Vol 9 (12) ◽  
pp. 9858-9872
Author(s):  
Krzysztof Ślot ◽  
Łukasz Bronakowski ◽  
Jaroslaw Cichosz ◽  
Hyongsuk Kim
Keyword(s):  
Poincaré Mapping ◽  
Poincare Mapping ◽  
Voiced Speech ◽  
Speech Segments

scholarly journals On Usable Speech Detection by Linear Multi-Scale Decomposition for Speaker Identification

2016 ◽  
Vol 6 (6) ◽  
pp. 2766
Author(s):  
Wajdi Ghezaiel ◽  
Amel Ben Slimane ◽  
Ezzedine Ben Braiek
Keyword(s):  
Speech Processing ◽  
Speaker Identification ◽  
Identification System ◽  
Discrete Wavelet ◽  
Speech Detection ◽  
Multi Scale ◽  
Speech Data ◽  
Pitch Information ◽  
Novel Concept ◽  
Speech Segments

<p>Usable speech is a novel concept of processing co-channel speech data. It is proposed to extract minimally corrupted speech that is considered useful for various speech processing systems. In this paper, we are interested for co-channel speaker identification (SID). We employ a new proposed usable speech extraction method based on the pitch information obtained from linear multi-scale decomposition by discrete wavelet transform. The idea is to retain the speech segments that have only one pitch detected and remove the others. Detected Usable speech was used as input for speaker identification system. The system is evaluated on co-channel speech and results show a significant improvement across various Target to Interferer Ratio (TIR) for speaker identification system.</p>

On Usable Speech Detection by Linear Multi-Scale Decomposition for Speaker Identification

2016 ◽  
Vol 6 (6) ◽  
pp. 2766
Author(s):  
Wajdi Ghezaiel ◽  
Amel Ben Slimane ◽  
Ezzedine Ben Braiek
Keyword(s):  
Speech Processing ◽  
Speaker Identification ◽  
Identification System ◽  
Discrete Wavelet ◽  
Speech Detection ◽  
Multi Scale ◽  
Speech Data ◽  
Pitch Information ◽  
Novel Concept ◽  
Speech Segments

<p>Usable speech is a novel concept of processing co-channel speech data. It is proposed to extract minimally corrupted speech that is considered useful for various speech processing systems. In this paper, we are interested for co-channel speaker identification (SID). We employ a new proposed usable speech extraction method based on the pitch information obtained from linear multi-scale decomposition by discrete wavelet transform. The idea is to retain the speech segments that have only one pitch detected and remove the others. Detected Usable speech was used as input for speaker identification system. The system is evaluated on co-channel speech and results show a significant improvement across various Target to Interferer Ratio (TIR) for speaker identification system.</p>

scholarly journals A Statistical Approach for Voiced Speech Detection

2011 ◽  
pp. 297-300
Author(s):  
Mihir Narayan Mohanty ◽  
Aurobinda Routray ◽  
Prithviraj Kabisatpathy
Keyword(s):  
Decision Rule ◽  
High Performance ◽  
Signal To Noise Ratio ◽  
A Priori ◽  
Ratio Test ◽  
Noisy Environments ◽  
Speech Detection ◽  
Voiced Speech ◽  
Variable Rate Speech Coding ◽  
Noise Statistics

Detection of Voice in speech signal is a challenging problem in developing high-performance systems used in noisy environments. In this paper, we present an efficient algorithm for robust voiced speech detection and for the application to variable-rate speech coding. The key idea of the algorithm is considering speech energy and zero crossings rate (ZCR) information simultaneously when processing speech signals and finding the end point of the signal. Next to it a decision rule and a background noise statistics estimator, by applying a statistical model. A robust decision rule is derived from the generalized likelihood ratio test (LRT) by assuming that the noise statistics are known a priori. The algorithm is most efficient for the time-varying noise. According to our simulation results, the proposed algorithm shows significantly better performance in low signal-to-noise ratio and in noisy environments.

Sign in / Sign up

Export Citation Format

Share Document