• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.12
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• pp.217-223
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• 2013

This paper proposes a spatial audio reproduction system based on audio fingerprinting that combines the audio fingerprinting and the spatial audio processing. In the proposed system, a salient audio peak pair fingerprint based on modulation spectrum improves the accuracy of the audio fingerprinting system in real noisy environments and spatial audio information as metadata gives a listener a sensation of being listening to the sound in the space, where the sound is actually recorded.

• Proceedings of the IEEK Conference
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• 2002.07a
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• pp.454-457
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• 2002

In this paper, we proposed digital audio watermarking algorithm for high quality audio. Nowadays, digital watermark used to confirm to digital copyright protection, not only digital image but also digital audio is active in the digital watermarking study. In this paper, we proposed digital audio watermarking algorithm using psychoacoustics model and MDCT/IMDCT (Modified Discrete Cosine Transform/Inverse Modified Discrete Cosine Transform) for the high quality audio watermark. In the proposed scheme, we used to 441KHz, 128kbps and stereo audio data for audio watermarking algorithm. Audio data is passed by MDCT; watermark can be inserted into the frequency domain with 256,1024 and 2048 interval.

• Journal of information and communication convergence engineering
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• v.5 no.3
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• pp.245-248
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• 2007

In this paper, we research the content-based analysis and classification according to the composition of the feature parameter data base for the audio data to implement the audio data index and searching system. Audio data is classified to the primitive various auditory types. We described the analysis and feature extraction method for the feature parameters available to the audio data classification. And we compose the feature parameters data base in the index group unit, then compare and analyze the audio data centering the including level around and index criterion into the audio categories. Based on this result, we compose feature vectors of audio data according to the classification categories, and simulate to classify using discrimination function.

• Proceedings of the IEEK Conference
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• 2000.06b
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• pp.181-184
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• 2000

In this paper, we described a design of the input buffer system for efficiently dealing with MPEG audio bitstream to demux header and side information, audio data. In order to overcome the limitations of fixed-word manipulation in bitstream demuxing, we proposed a new variable length bit retrieval system with FSM sequencer supporting MPEG audio frame format, and serial buffer demuxing audio stream, FIFO circular buffer including header and side information.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.4
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• pp.1538-1552
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• 2021

Machine learning models are vulnerable to adversarial examples generated by adding a deliberately designed perturbation to a benign sample. Particularly, for automatic speech recognition (ASR) system, a benign audio which sounds normal could be decoded as a harmful command due to potential adversarial attacks. In this paper, we focus on the countermeasures against audio adversarial examples. By analyzing the characteristics of ASR systems, we find that frame offsets with silence clip appended at the beginning of an audio can degenerate adversarial perturbations to normal noise. For various scenarios, we exploit frame offsets by different strategies such as defending, detecting and hybrid strategy. Compared with the previous methods, our proposed method can defense audio adversarial example in a simpler, more generic and efficient way. Evaluated on three state-of-the-arts adversarial attacks against different ASR systems respectively, the experimental results demonstrate that the proposed method can effectively improve the robustness of ASR systems.

• ETRI Journal
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• v.28 no.4
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• pp.509-512
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• 2006

In a real environment, sound recordings are commonly distorted by channel and background noise, and the performance of audio identification is mainly degraded by them. Recently, Philips introduced a robust and efficient audio fingerprinting scheme applying a differential (high-pass filtering) to the frequency-time sequence of the perceptual filter-bank energies. In practice, however, the robustness of the audio fingerprinting scheme is still important in a real environment. In this letter, we introduce alternatives to the frequency-temporal filtering combination for an extension method of Philips' audio fingerprinting scheme to achieve robustness to channel and background noise under the conditions of a real situation. Our experimental results show that the proposed filtering combination improves noise robustness in audio identification.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.62 no.12
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• pp.1764-1770
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• 2013

Use of the 5.1 channel audio signals suitable for the television system is improper for the radio broadcasting system, which uses the stereo audio system. Therefore, it is necessary to develop an audio down-mixer to convert 5.1 multi-channel audio signals to stereo signals for radio broadcasting. In this paper, a development of an audio down-mixer was carried out to convert 5.1 multi-channel audio signals to stereo signals. The down-mixer which was developed can use the audio signals separated from video signals, including sound signals or individual signals provided from 3-channel AES/EBU signals including Left(L), Right(R), Left Surround(Ls), Right Surround(Rs), Center(C) and Low Frequency Effect(Lfe) sounds as mixer inputs.

• Proceedings of the IEEK Conference
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• 2000.06c
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• pp.125-128
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• 2000

In this paper, we proposed the high quality digital audio watermarking algorithm in the frequency domain. The spread spectrum technique is used to encrypted a stream of information by spreading the data as much of the frequency spectrum as possible. It's technique adapt well to data hiding in audio signal. We have used the perceptual model and MDCT/IMDCT for the high qualify digital audio watermarking. The proposed watermark algorithm preserved high quality audio data from watermark signal.

• Proceedings of the IEEK Conference
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• summer
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• pp.233-236
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• 2004

This paper proposes new method for the enhancement of nonexistent high frequency spectral contents from low sample rate audio signal. For example, Due to the protocol constraint, the audio bandwidth of MP3 is restricted to 16Khz. Although band-restricted MP3 audio provide savings of storage space and network bandwidth, it suffers a major problem of a loss in high frequency fidelity such as localization, ambient information, and bright nature of audio. This paper provides a new mathematical analysis for the adaptive estimation of the high frequency contents based on the nature of the input low sample rate audio. Proposed method can be worked globally to any kind of audio such as speech and music that are restricted by sampling rate and bandwidth.

• Proceedings of the IEEK Conference
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• 2003.11b
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• pp.243-246
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• 2003

In this paper, we propose a new digital audio watermarking technique with the wavelet transform. The watermark is embedded by eliminating unnecessary information of audio signal based on human auditory system (HAS). This algorithm is an audio watermarking method, which does not require any original audio information in watermark extraction process. In this paper, the masking effect is used for audio watermarking, that is, post-tempera] masking effect. We construct the window with the synchronization signal and we extract the best frame in the window by using the zero-crossing rate (ZCR) and the energy of the audio signal. The watermark may be extracted by using the correlation of the watermark signal and the portion of the frame. Experimental results show good robustness against MPEG1-layer3 compression and other common signal processing manipulations. All the attacks are made after the D/A/D conversion.