Showing papers on "Modified discrete cosine transform published in 2021"

An SVD-based adaptive robust speech steganography using MDCT coefficient

Abstract: Speech is one of the essential ways of communication. The study of speech steganography provides great value in information security. To improve imperceptibility and robustness of speech steganography, the characteristics of speech signals should be fully taken into account. In this paper, a robust speech steganographic scheme based on Singular Value Decomposition (SVD) and Modified Discrete Cosine Transform (MDCT) is proposed. Firstly, Voice Activity Detector (VAD) is used to detect voiced frames from speech signals, along with MDCT with Kaiser Bessel Derived (KBD) window being performed on each frame. Then the MDCT coefficients are selected from a certain frequency range and divided into a pair of segments. The two largest singular values of the paired segments are modified respectively according to their value difference to embed secret message. The thresholds are adaptively adjusted according to the largest singular values. Extensive experiments are carried out to compare the proposed method with three other methods from imperceptibility, robustness, capacity, and security. The experimental results show that under the simulation parameters β = 320, Nk = 58, fl = 100 Hz, fh = 3 kHz, and α = 0.61, the proposed method has striking advantages to resist common robust attacks and the state-of-the-art steganalysis attacks while maintaining good imperceptibility.

Spoofed Voice Detection using Dense Features of STFT and MDCT Spectrograms

Abstract: Attestation of audio signals for recognition of forgery in voice is challenging task. In this research work, a deep convolutional neural network (CNN) is utilized to detect audio operations i.e. pitch shifted and amplitude varied signals. Short-time Fourier transform (STFT) and Modified Discrete Cosine Transform (MDCT) features are chosen for audio processing and their plotted patterns are fed to CNN. Experimental results show that our model can successfully distinguish tampered signals to facilitate the audio authentication on TIMIT dataset. Proposed CNN architecture can distinguish spoofed voices of shifting pitch with accuracy of 97.55% and of varying amplitude with accuracy of 98.85%.

MP3net: coherent, minute-long music generation from raw audio with a simple convolutional GAN.

Abstract: We present a deep convolutional GAN which leverages techniques from MP3/Vorbis audio compression to produce long, high-quality audio samples with long-range coherence. The model uses a Modified Discrete Cosine Transform (MDCT) data representation, which includes all phase information. Phase generation is hence integral part of the model. We leverage the auditory masking and psychoacoustic perception limit of the human ear to widen the true distribution and stabilize the training process. The model architecture is a deep 2D convolutional network, where each subsequent generator model block increases the resolution along the time axis and adds a higher octave along the frequency axis. The deeper layers are connected with all parts of the output and have the context of the full track. This enables generation of samples which exhibit long-range coherence. We use MP3net to create 95s stereo tracks with a 22kHz sample rate after training for 250h on a single Cloud TPUv2. An additional benefit of the CNN-based model architecture is that generation of new songs is almost instantaneous.

Detection of AAC compression using MDCT-based features and supervised learning

Abstract: Audio files are frequent targets of malicious users who seek illegal profit trading with fake-quality content. For increasing the confidence in the integrity of audio files, the detection of fake-q...

A Hybrid Transform for Reduction of Peak to Average Power Ratio in OFDM System

Abstract: The performance of orthogonal frequency multiplexing (OFDM) communication systems is affected by the peak to average power ratio (PAPR). The research work uses a hybrid transform for reducing this PAPR value. In recent years, OFDM is more prevalent in the research field, particularly in wireless communication. OFDM system is found to have a high PAPR value. This high PAPR leads to nonlinear distortions that result in low power efficiency. Hence there is a need to minimize PAPR. Hadamard transform is a commonly used technique for the reduction of PAPR. However, greater efficiency can be carried out using a hybrid way to reducing the PAPR of the signals applying OFDM. Modified Discrete Cosine Transform (MDCT) combined with nonlinear companding technique, is suggested to minimize PAPR, described as a hybrid transform. It is shown that the hybrid transform achieves a better lessening of PAPR and minimized Bit Error Rate (BER) in the OFDM communication system when compared with the basic OFDM, Hadamard transforms, and Companding technique.

Frequency Domain Long-Term Prediction for Low Delay General Audio Coding

Abstract: In this paper we propose a long-term prediction method for low delay transform domain general audio coders. This Frequency Domain Joint Harmonics Prediction (FDJHP) method operates directly in the Modified Discrete Cosine Transform (MDCT) domain and can enhance the coding efficiency, even under very low frequency resolutions. We compare this new method with state-of-the-art MDCT based methods by analyzing bitrate savings and by a listening test using test signals with strong harmonic components. The results indicate that it outperforms an existing method, which also directly operates in the frequency domain. Additionally, we show how it can be combined with the existing techniques into an adaptive system, where the different methods can complement each other.

Window analysis / synthesis function for modulated transform with overlapping

Abstract: FIELD: computer equipment.SUBSTANCE: invention relates to computer engineering for processing audio data. Technical result is achieved by performing synthesis based on modified discrete cosine transform (MDCT) for conversion of FD-presentation of information signal or its processed version into representation in time domain (TD-representation) using synthesis window function (90), having meander section (94), which transitions linear function in corresponding at least four points (No. 1, No. 2, No. 3, No. 4), wherein synthesis window function (90, 290) is defined such that in meandering section: exceed linear function in first interval between first intersection point and second intersection point; be lower than linear function in second interval between second intersection point and third intersection point; exceed the linear function in the third interval between the third intersection point and the fourth intersection point.EFFECT: technical result consists in excluding suboptimal frequency characteristic by eliminating rupture differentiation of information signal.43 cl, 33 dwg