• Proceedings of the IEEK Conference
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• 2002.07a
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• pp.478-481
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• 2002

In this paper, the zerotrees of DWT is proposed to be used in a speech based digital watermarking for digital images. Since in this research work the raw speech and its content are used as a watermark signal, in the watermarking scheme, the PCM coded speech signal is embedded into a sequence of images. The performance of the scheme is evaluated by the PSNR obtained from the watermarked images and the strength of attacks the embedded speech signal can survive. Moreover, since in this research work the contents contained in the speech is used to identify the specific information hidden in the embedded signal. The speech signal after being extracted from the watermarked images is played back to the listeners to determine whether its content is intelligible or not. The experimental results show impressive performance of the scheme implementing our proposed technique, judged by the higher robustness obtained form the embedded signal against various types of attack, including brightness/contrast enhancement, Twirling, highpass filtering and JPEG compression standard.

• Proceedings of the IEEK Conference
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• 2002.07a
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• pp.466-469
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• 2002

Using intelligent information contained within the speech to identify the specific hidden data in the watermarked multimedia data is considered to be an efficient method to achieve the speech digital watermarking. This paper presents the performance comparison between various types of speech codec in order to determine an appropriate one to be used in digital watermarking applications. In the experiments, the speech signal encoded by four different types of speech codec, namely CELP, GSM, SBC and G.723.1codecs is embedded into a grayscale image, and theirs performance in term of speech recognition are compared. The method for embedding the speech signal into the host data is borrowed from a watermarking method based on the zerotrees of wavelet packet coefficients. To evaluate efficiency of the speech codec used in watermarking applications, the speech signal after being extracted from the attacked watermarked image will be played back to the listeners, and then be justified whether its content is intelligible or not.

• The Journal of the Acoustical Society of Korea
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• v.15 no.1
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• pp.93-101
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• 1996

In this paper, we implement the system for speech processing to provide the subscribers who are using the telephone network with better speech services. We develop the specified board which is processing speech signal and devise the system which carries out storing and replaying the speech signal under the condition that one master board controls multiple DSP(Digital Signal Processing) boards using VME bus. We use CPU30 board as a maste board and develop SPM(Signal Processing Module) board as a DSP board and then evaluate performance of the system.

• Proceedings of the KIEE Conference
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• 1987.07b
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• pp.1583-1586
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• 1987

In the study for effective speech control we designed a personal computer system with A/D converter in which the speech signal is transformed by digital data displayed graphically on the moniter and with a D/A converter in which the digital data is transformed into speech signal which people can hear. We analyzed the character of the speech signal produced by the system. We designed the adaptive noise cancel algorithm so that noise and Interference are cancelled whenever the speech signal is recognized by the computer system. This is a basic system for artificial Intelligence.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.30B no.10
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• pp.35-41
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• 1993

In this paper, a new speech enhancement method for speech signal corrupted by environmental noise is proposed. Two signals are obtained from the microphone and from the accelerometer attached to the neck, respectively. Since two signals are generated from same source signal, both signals are closely correlated. And environmental noise has no effect on the accelerometer signal. The speech enhancement system identifies the optimum linear system between two signals on the basis of the dependence between the signals. The enhanced speech can be obtained by filtering the noise-free accelerometer signal. Since the characteristcs of the speech signal and environmental noise are changing with time, adaptive filtering system has to be used for characterizing the time-varing system. Simulation results show 7dB enhancement with 0dB speech signal level relative to the white noise.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.42 no.3 s.303
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• pp.121-128
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• 2005

On the research field for speech signal, neural network mainly uses for the category classification in speech recognition and applies to signal processing. Accordingly, this paper proposes a noise reduction system using a time-delay neural network, which implements the mapping from the space of speech signal degraded by noise to the space of clean speech signal. It is confirmed that this method is effective for speech degraded not only by white noise but also by colored noise using the noise reduction system, which restores the amplitude component of fast Fourier transform.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.5
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• pp.2588-2609
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• 2019

Speech homomorphic encryption has become one of the key components in secure speech storing in the public cloud computing. The major problem of speech homomorphic encryption is the huge data expansion of speech cipher-text. To address the issue, this paper presents a speech homomorphic encryption scheme with less data expansion, which is a probabilistic statistics and addition homomorphic cryptosystem. In the proposed scheme, the original digital speech with some random numbers selected is firstly grouped to form a series of speech matrix. Then, a proposed matrix encryption method is employed to encrypt that speech matrix. After that, mutual information in sample speech cipher-texts is reduced to limit the data expansion. Performance analysis and experimental results show that the proposed scheme is addition homomorphic, and it not only resists statistical analysis attacks but also eliminates some signal characteristics of original speech. In addition, comparing with Paillier homomorphic cryptosystem, the proposed scheme has less data expansion and lower computational complexity. Furthermore, the time consumption of the proposed scheme is almost the same on the smartphone and the PC. Thus, the proposed scheme is extremely suitable for secure speech storing in public cloud computing.

• Journal of Digital Convergence
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• v.11 no.7
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• pp.209-214
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• 2013

Improve the recognition performance of speech recognition systems as a method for recognizing human listening skills were incorporated into the system. In noisy environments by separating the speech signal and noise, select the desired speech signal. but In terms of practical performance of speech recognition systems are factors. According to recognized environmental changes due to noise speech detection is not accurate and learning model does not match. In this paper, to improve the speech recognition feature extraction using gamma tone and learning model using acoustic model was proposed. The proposed method the feature extraction using auditory scene analysis for human auditory perception was reflected In the process of learning models for recognition. For performance evaluation in noisy environments, -10dB, -5dB noise in the signal was performed to remove 3.12dB, 2.04dB SNR improvement in performance was confirmed.

• ETRI Journal
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• v.35 no.4
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• pp.697-705
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• 2013

Emerging trends in the area of digital very large scale integration (VLSI) signal processing can lead to a reduction in the cost of the cochlear implant. Digital signal processing algorithms are repetitively used in speech processors for filtering and encoding operations. The critical paths in these algorithms limit the performance of the speech processors. These algorithms must be transformed to accommodate processors designed to be high speed and have less area and low power. This can be realized by basing the design of the auditory filter banks for the processors on digital VLSI signal processing concepts. By applying a folding algorithm to the second-order digital gammatone filter (GTF), the number of multipliers is reduced from five to one and the number of adders is reduced from three to one, without changing the characteristics of the filter. Folded second-order filter sections are cascaded with three similar structures to realize the eighth-order digital GTF whose response is a close match to the human cochlea response. The silicon area is reduced from twenty to four multipliers and from twelve to four adders by using the folding architecture.

• Journal of Broadcast Engineering
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• v.23 no.1
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• pp.86-92
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• 2018

In this paper, we propose a method for coding history detection of digital speech signal. In digital speech communication and storage, the signal is encoded to reduce the number of bits. Therefore, when a speech signal waveform is given, we need to detect its coding history so that we can determine whether the signal is an original or an coded one, and if coded, determine the number of times of coding. In this paper, we propose a coding history detection method for 12.2kbps AMR codec in terms of original, single coding, and double coding. The proposed method extracts a speech-specific feature vector from the given speech, and models the feature vector using a deep neural network. We confirm that the proposed feature vector provides better performance in coding history detection than the feature vector computed from the general spectrogram.