Redirigiendo al acceso original de articulo en 20 segundos...
ARTÍCULO
TITULO

Source Separation via Spectral Masking for Speech Recognition Systems

Gustavo Fernandes Rodrigues    
Thiago de Souza Siqueira    
Ana Cláudia Silva de Souza    
Hani Camille Yehia    

Resumen

In this paper we present an insight into the use of spectral masking techniques in time-frequency domain, as a preprocessing step for the speech signal recognition. Speech recognition systems have their performance negatively affected in noisy environments or in the presence of other speech signals. The limits of these masking techniques for different levels of the signal-to-noise ratio are discussed. We show the robustness of the spectral masking techniques against four types of noise: white, pink, brown and human speech noise (bubble noise). The main contribution of this work is to analyze the performance limits of recognition systems  using spectral masking. We obtain an increase of 18% on the speech hit rate, when the speech signals were corrupted by other speech signals or bubble noise, with different signal-to-noise ratio of approximately 1, 10 and 20 dB. On the other hand, applying the ideal binary masks to mixtures corrupted by white, pink and brown noise, results an average growth of 9% on the speech hit rate, with the same different signal-to-noise ratio. The experimental results suggest that the masking spectral techniques are more suitable for the case when it is applied a bubble noise, which is produced by human speech, than for the case of applying white, pink and brown noise.

 Artículos similares

       
 
Tingkai Dai and Bo Zhang    
Shock wave/turbulent boundary layer interaction (SBLI) is one of the most common physical phenomena in transonic wing and supersonic aircraft. In this study, the compression ramp SBLI (CR-SBLI) was simulated at a 24° corner at Mach 2.84 using the open-so... ver más
Revista: Aerospace

 
Yu Zhang, Maoshen Jia, Xinyu Jia and Tun-Wen Pai    
Multiple sound source separation in a reverberant environment has become popular in recent years. To improve the quality of the separated signal in a reverberant environment, a separation method based on a DOA cue and a deep neural network (DNN) is propo... ver más
Revista: Applied Sciences

 
Han Li, Kean Chen, Lei Wang, Jianben Liu, Baoquan Wan and Bing Zhou    
Thanks to the development of deep learning, various sound source separation networks have been proposed and made significant progress. However, the study on the underlying separation mechanisms is still in its infancy. In this study, deep networks are ex... ver más
Revista: Applied Sciences

 
Csaba Fogarassy, Nguyen Huu Hoang and Kinga Nagy-Pércsi    
The waste-to-energy programs that have taken place in recent years present a daunting picture in terms of sustainable material management. The incineration of much organic and unorganized waste in metropolitan waste treatment facilities is not meet with ... ver más
Revista: Applied Sciences

 
Marta Ribeiro, Joost Ellerbroek and Jacco Hoekstra    
Current predictions on future drone operations estimate that traffic density orders of magnitude will be higher than any observed in manned aviation. Such densities redirect the focus towards elements that can decrease conflict rate and severity, with sp... ver más
Revista: Aerospace