Ethernet TCP/IP-Based Audio Interface for DSP System Verification

Pekez, Nenad; Popovic, Andrej; Kovačević, Jelena

doi:10.1109/mce.2020.2988616

Cited by 8 publications

(2 citation statements)

References 4 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…DSPs dominate the market with their software and hardware resources suitable for digital signal processing. (e use of DSP chips to develop digital audio processing devices takes into account the disadvantages of low resource utilization of FPGAs and long development cycles of dedicated audio processing chips and they are widely used in modern digital signal processing [14].…”

Section: Introductionmentioning

confidence: 99%

Research and DSP Implementation of Speech Enhancement Technology Based on Dynamic Mixed Features and Adaptive Mask

Yang

Tang

2022

Journal of Electrical and Computer Engineering

View full text Add to dashboard Cite

A deep learning speech enhancement algorithm based on dynamic hybrid feature and adaptive mask and DSP implementation is proposed in this paper, which solves the problem of feature loss and improves the performance of speech enhancement. The dynamic features incorporate the log Mel power spectrum, Mel cepstral coefficients, and Multiresolution Auditory Cepstral Coefficients (MRACC) and capture the speech transient information by deriving the derivatives to comprehensively represent the nonlinear structure of speech and reduce distortion. To make the system improve the speech quality while reducing the speech distortion as much as possible, a soft mask that can be adaptively adjusted considering the signal-to-noise ratio information is proposed, which can be automatically adjusted according to the different speech signal-to-noise ratio information to obtain the mask value under the corresponding signal-to-noise ratio conditions, and phase difference information that can improve the speech intelligibility is incorporated in it. Then, an improved deep neural network model is designed to effectively improve the speech enhancement performance. Finally, the hardware and algorithm software design of the DSP-based speech enhancement system is given. Experimental simulations are carried out for multiple voices in different noise backgrounds. The experimental results indicate that the performance indexes of the proposed method are significantly improved compared with the existing speech enhancement methods, which verifies the feasibility and superiority of the proposed method.

show abstract

Section: Introductionmentioning

confidence: 99%

Research and DSP Implementation of Speech Enhancement Technology Based on Dynamic Mixed Features and Adaptive Mask

Yang

Tang

2022

Journal of Electrical and Computer Engineering

View full text Add to dashboard Cite

show abstract

“…developed audio grabber, named "Real Time Audio Grabber" (RT-AG)[19]-[21]; 4. Nvidia graphic card is used to generate HDMI input, as some IP providers specifically rely on an application for input stream generation that is based on this card; 5.…”

mentioning

confidence: 99%

Smart Multi-Agent Framework for Automated Audio Testing

Kovačević

Radujko

Djukic

et al. 2023

ELEKTRON ELEKTROTECH

View full text Add to dashboard Cite

With the widespread use of embedded software in consumer electronics, automotive industry, medical devices, and industrial environments, embedded software testing is gaining significance as an indispensable part of development and deployment of embedded products. With more than 20 years of research, development, and testing of various consumer technologies and products based on digital signal processors (DSPs) and advanced reduced instruction set computers (ARMs), we obtained insight into typical embedded development process and testing, and the pros and cons of various testing approaches and environments. In this paper, we propose the Smart Multi-Agent Framework based on IoT and Jenkins agents, customised for audio technologies in the Home Audio domain. We evaluated our solution on several complex immersive audio technologies implemented on a multicore DSP. Our uniform, customised, fully automated approach proved to be time efficient, error resilient, easy to replicate and use across all development, certification, and deployment phases of the product life cycle.

show abstract