• Proceedings of the Korean Society of Computer Information Conference
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• 2014.01a
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• pp.89-92
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• 2014

This paper presents a secure and blind adaptive audio watermarking algorithm based on Empirical Mode Decomposition (EMD). The audio signal is divided into frames and each one is decomposed adaptively, by EMD, into several Intrinsic Mode Functions (IMFs). The watermark and the synchronization codes are then embedded into the extrema of the last IMF. The experimental results show that the proposed method has good imperceptibility and robustness against signal processing attacks.

• ETRI Journal
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• v.40 no.1
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• pp.133-145
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• 2018

Robustness, payload, and imperceptibility of audio watermarking algorithms are contradictory design issues with high-level security of the watermark. In this study, the major issue in achieving high payload along with adequate robustness against challenging signal-processing attacks is addressed. Moreover, a security code has been strategically used for secure transmission of data, providing tamper detection at the receiver end. The high watermark payload in this work has been achieved by using the complementary features of third-level detailed coefficients of discrete wavelet transform where the human auditory system is not sensitive to alterations in the audio signal. To counter the watermark loss under challenging attacks at high payload, Daubechies wavelets that have an orthogonal property and provide smoother frequencies have been used, which can protect the data from loss under signal-processing attacks. Experimental results indicate that the proposed algorithm has demonstrated adequate robustness against signal processing attacks at 4,884.1 bps. Among the evaluators, 87% have rated the proposed algorithm to be remarkable in terms of transparency.

• Annual Conference of KIPS
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• 2009.11a
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• pp.243-244
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• 2009

So far, many researches have been conducted in the area of audio based context recognition. Nevertheless, most of them are based on existing feature extraction techniques derived from linear signal processing such as Fourier transform, wavelet transform, linear prediction... Meanwhile, environmental audio signal may potentially contains non-linear dynamic properties. Therefore, it is a big potential to utilize non-linear dynamic signal processing techniques in audio based context recognition.

• International journal of advanced smart convergence
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• v.13 no.3
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• pp.1-12
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• 2024

Recently, Audio systems transform the configuration of conventional sound reinforcement and public address systems using audio over internet protocol (AoIP), whereby audio signals are transmitted and received based on internet protocol (IP). Currently, AoIP technologies are leading the audio market, and various technologies have been released. Audio networks and the control hierarchy over peer-to-peer (Anchor) technology based on AoIP transmit and receive audio signals over a wide bandwidth without an audio mixer. Audio system based on Anchor technology is constructed by connecting the on-site audio center (OAC), a device that can transmit and receive audio sources and output equipment over IP. Receiving OAC of the Anchor technology can receive and mix audio signals transmitted from different IPs; consequently, novel audio systems can be configured by replacing conventional audio mixers. However, the Anchor technology does not have an equalizer function for improving the quality of audio equipment. Therefore, tone distortion may occur owing to signal loss between equipment, poor audio-signal clarity, and howling due to audio deformation according to different architectural structures and environments. In this study, we implemented an audio effect device capable of tone control using the Audio Processor Core. Using Anchor technology, tone control was realized through an audio effect device in the receiving OAC. The output of the incoming OAC was received by the audio effect device, which adjusted the tone and then outputted it. Thus, the tone issues in Anchor technology were overcome by the receiving OAC and audio effect devices. In future, audio system configurations using Anchor technology could be the standard for audio equipment.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.41 no.6
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• pp.271-278
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• 2004

In this paper, we propose a content-based audio genre classification algorithm that automatically classifies the query audio into five genres such as Classic, Hiphop, Jazz, Rock, Speech using digital sign processing approach. From the 20 seconds query audio file, the audio signal is segmented into 23ms frame with non-overlapped hamming window and 54 dimensional feature vectors, including Spectral Centroid, Rolloff, Flux, LPC, MFCC, is extracted from each query audio. For the classification algorithm, k-NN, Gaussian, GMM classifier is used. In order to choose optimum features from the 54 dimension feature vectors, SFS(Sequential Forward Selection) method is applied to draw 10 dimension optimum features and these are used for the genre classification algorithm. From the experimental result, we can verify the superior performance of the proposed method that provides near 90% success rate for the genre classification which means 10%∼20% improvements over the previous methods. For the case of actual user system environment, feature vector is extracted from the random interval of the query audio and it shows overall 80% success rate except extreme cases of beginning and ending portion of the query audio file.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.17 no.6
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• pp.572-579
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• 1992

In this thesis, feedback circuit and FM detector applied to superheterodyne receiver to extract audio signal without random noise Is implemented. The feedback loop circuit converts 45MHz received signal to 4SiKHz If signal containing mess-age without random noise. Also the feedback loop provides the End local frequency, so narrowband BPF which is containing maximum Doppler frequency without message Is needed. Finally, quadrature FM detector extract audio signal by synthesis o350" shifted signal and ampli-tude limited signal. RSSI characteristics is measured and audio characteristics Is compared with existing If module.

• ETRI Journal
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• v.31 no.6
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• pp.732-740
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• 2009

This paper describes the implementation of a digital audio effect system-on-a-chip (SoC), which integrates an embedded digital signal processor (DSP) core, audio codec intellectual property, a number of peripheral blocks, and various audio effect algorithms. The audio effect SoC is developed using a software and hardware co-design method. In the design of the SoC, the embedded DSP and some dedicated hardware blocks are developed as a hardware design, while the audio effect algorithms are realized using a software centric method. Most of the audio effect algorithms are implemented using a C code with primitive functions that run on the embedded DSP, while the equalization effect, which requires a large amount of computation, is implemented using a dedicated hardware block with high flexibility. For the optimized implementation of audio effects, we exploit the primitive functions of the embedded DSP compiler, which is a very efficient way to reduce the code size and computation. The audio effect SoC was fabricated using a 0.18 ${\mu}m$ CMOS process and evaluated successfully on a real-time test board.

• Journal of the Institute of Electronics and Information Engineers
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• v.49 no.11
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• pp.149-156
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• 2012

A digital input class-D audio amplifier is presented for digital hearing aid. The class-D audio amplifier is composed of digital and analog circuits. The analog circuit converts a digital input to a analog audio signal (DAC) with noise suppression in the audio band. An interpolated digital delta-sigma modulator is used to convert data types between digital signal processor (DSP) and digital-to-analog converter (DAC). An 16-bit, 25-kbps pulse code modulated (PCM) input is interpolated to 16-bit, 50-kbps by a digital filter. The output signal of interpolation filter is noise-shaped by a third-order digital sigma-delta modulator (SDM). As a result, 1.5-bit, 3.2-Mbps signal is applied to simple digital to analog converter.

• Proceedings of the KIEE Conference
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• 2004.11c
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• pp.605-607
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• 2004

A class D digital audio amplifier with small size, low cost, and high quality is positively necessary in the multimedia era made of home theater system and the digital audio broadcasting (DAB). It is impossible to analyze the stability of the digital audio amplifier, which is based on the PWM signal processing. To solve this problem, the digital audio amplifier is analyzed using variable structure control theory which is one of nonlinear system theories. Moreover, the magnitude and the frequency of ripple signal, which generated by hysteresis in the comparator, is obtained using describing function which is useful to represent the input-output relation of nonlinear system.

• Journal of The Institute of Information and Telecommunication Facilities Engineering
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• v.5 no.1
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• pp.37-42
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• 2006

A reversible audio watermarking algorithm is presented in this paper. This algorithm transforms the audio signal with the integer wavelet transform first in order to enhance the correlation between neighbor audio samples. Audio signal has low correlation between neighbor samples, which makes it difficult to apply difference expansion scheme. Second, a novel difference expansion scheme is used to embed more data by reducing the size of location map. Therefore, the difference expansion scheme used in this paper theoretically secures high embedding capacity under low perceptual distortion. Experiments show that this scheme can hide large number of information bits and keeps high perceptual quality.