Currently, an increasing number of tasks in speech emotion recognition rely on the analysis of both speech and text features. However, there remains a paucity of research exploring the potential of leveraging large language models like GPT-3 to enhance emotion recognition. In this investigation, we harness the power of the GPT-3 model to extract semantic information from transcribed texts, generating text modal features with a dimensionality of 1536. Subsequently, we perform feature fusion, combining the 1536-dimensional text features with 1188-dimensional acoustic features to yield comprehensive multi-modal recognition outcomes. Our findings reveal that the proposed method achieves a weighted accuracy of 79.62% across the four emotion categories in IEMOCAP, underscoring the considerable enhancement in emotion recognition accuracy facilitated by integrating large language models.

Orthogonal frequency division multiplexing (OFDM) is very sensitive to the frequency errors caused by phase noise and Doppler shift. These errors will disturb the orthogonality among subcarriers and cause intercarrier interference (ICI). A simple method to combat ICI is proposed in this letter. The main idea is to map each data symbol onto a couple of subcarriers rather to a single subcarrier. Different from the conventional adjacent coupling and symmetric coupling methods, the frequency diversity can be utilized more efficiently by the proposed adaptive coupling method based on optimal subcarrier spacing. Numerical results show that our proposed method provides a robust signal-to-noise ratio (SNR) improvement over the conventional coupling methods.

In this paper, we present a perceptual distortion measure (PDM) for polygon-based shape coding. We model the PDM as the salience of relevance triangle, and express the PDM by using three properties derived from the salience of visual part. Performance analysis and experimental results show that our proposal can improve the quality of the shape reconstruction when the object contour has sharp protrusions.

This paper proposes several improved Side-channel cube attacks (SCCAs) on PRESENT-80/128 under single bit leakage model. Assuming the leakage is in the output of round 3 as in previous work, we discover new results of SCCA on PRESENT. Then an enhanced SCCA is proposed to extract key related non-linear equations. 64-bit key for both PRESENT-80 and 128 can be obtained. To mount more effective attack, we utilize the leakage in round 4 and enhance SCCA in two ways. A partitioning scheme is proposed to handle huge polynomials, and an iterative scheme is proposed to extract more key bits. With these enhanced techniques, the master key search space can be reduced to 28 for PRESENT-80 and to 229 for PRESENT-128.

Downlink multiuser MIMO system has attracted considerable attention recently for its potential to increase the system capacity. However, due to the limitation on the number of transmit antennas, when there are more users than can be supported simultaneously in a cell, other multiple access schemes, such as TDMA, must be applied in combination with multiuser MIMO. In this paper, we aim to design practical user scheduling algorithms to maximize the system capacity. Because the brute-force search for optimal user allocation is computationally prohibitive, we propose three low complexity suboptimal scheduling algorithms that offer both low complexity and high performance.

A simple DFT-based noise variance estimator for orthogonal frequency division multiplexing access (OFDMA) systems is proposed. The conventional DFT-based estimator differentiates the channel impulse response and noise in the time domain. However, for partial frequency response, its time domain signal will leak to all taps due to the windowing effect. The noise and channel leakage power become mixed. In order to accurately derive the noise power, we propose a novel symmetric extension method to reduce the channel leakage power. This method is based on the improved signal continuity at the boundaries introduced by symmetric extension. Numerical results show that the normalized mean square error (NMSE) of our proposed method is significantly lower than that of the conventional DFT method.

The differential fault analysis of SOSEMNAUK was presented in Africacrypt in 2011. In this paper, we improve previous work with algebraic techniques which can result in a considerable reduction not only in the number of fault injections but also in time complexity. First, we propose an enhanced method to determine the fault position with a success rate up to 99% based on the single-word fault model. Then, instead of following the design of SOSEMANUK at word levels, we view SOSEMANUK at bit levels during the fault analysis and calculate most components of SOSEMANUK as bit-oriented. We show how to build algebraic equations for SOSEMANUK and how to represent the injected faults in bit-level. Finally, an SAT solver is exploited to solve the combined equations to recover the secret inner state. The results of simulations on a PC show that the full 384 bits initial inner state of SOSEMANUK can be recovered with only 15 fault injections in 3.97h.