Stability of filled cylindrical shell columns

This experimental investigation was conducted to study the stability of filled cylindrical shell columns. Two kinds of filler materials, flower clay (florist clay) and silica sand, were investigated. The cylindrical shells were made of 2024-T3 Reynolds aluminum tubing. Uniaxial compressive loading was applied directly to the filler materials through two loading rams, one at each end of the cylinder, (no loading was applied directly to the shell). Tests for investigating the load transmitting characteristics of the filler materials were performed, and the states of the stresses existing in the cylindrical shells were then obtained. The buckling formula for thin-walled cylindrical shells under internal hydrostatic pressure was compared with the experimental results of the cylinders filled with clay. The theory for thin-walled cylinders subjected to direct uniaxial compressive loading on the shells was compared with the results for the sand filled cylinders. It was necessary to introduce a reduction factor for effective length when sand was used the filler material. The tangent modulus formula was chosen to predict the buckling load of the filled cylinders beyond the elastic range of the material. The experimental results were found to be in good agreement with the theoretically predicted curves. Comparisons of the theoretical and experimental buckling loads are given graphically as functions of the length and the reciprocal of the square of the length --Abstract, pages ii-iii

InQSS: a speech intelligibility and quality assessment model using a multi-task learning network

Speech intelligibility and quality assessment models are essential tools for researchers to evaluate and improve speech processing models. However, only a few studies have investigated multi-task models for intelligibility and quality assessment due to the limitations of available data. In this study, we released TMHINT-QI, the first Chinese speech dataset that records the quality and intelligibility scores of clean, noisy, and enhanced utterances. Then, we propose InQSS, a non-intrusive multi-task learning framework for intelligibility and quality assessment. We evaluated the InQSS on both the training-from-scratch and the pretrained models. The experimental results confirm the effectiveness of the InQSS framework. In addition, the resulting model can predict not only the intelligibility scores but also the quality scores of a speech signal.Comment: accepted by Insterspeech 202

Noise robust speech emotion recognition with signal-to-noise ratio adapting speech enhancement

Speech emotion recognition (SER) often experiences reduced performance due to background noise. In addition, making a prediction on signals with only background noise could undermine user trust in the system. In this study, we propose a Noise Robust Speech Emotion Recognition system, NRSER. NRSER employs speech enhancement (SE) to effectively reduce the noise in input signals. Then, the signal-to-noise-ratio (SNR)-level detection structure and waveform reconstitution strategy are introduced to reduce the negative impact of SE on speech signals with no or little background noise. Our experimental results show that NRSER can effectively improve the noise robustness of the SER system, including preventing the system from making emotion recognition on signals consisting solely of background noise. Moreover, the proposed SNR-level detection structure can be used individually for tasks such as data selection

Voice Conversion Based on Cross-Domain Features Using Variational Auto Encoders

An effective approach to non-parallel voice conversion (VC) is to utilize deep neural networks (DNNs), specifically variational auto encoders (VAEs), to model the latent structure of speech in an unsupervised manner. A previous study has confirmed the ef- fectiveness of VAE using the STRAIGHT spectra for VC. How- ever, VAE using other types of spectral features such as mel- cepstral coefficients (MCCs), which are related to human per- ception and have been widely used in VC, have not been prop- erly investigated. Instead of using one specific type of spectral feature, it is expected that VAE may benefit from using multi- ple types of spectral features simultaneously, thereby improving the capability of VAE for VC. To this end, we propose a novel VAE framework (called cross-domain VAE, CDVAE) for VC. Specifically, the proposed framework utilizes both STRAIGHT spectra and MCCs by explicitly regularizing multiple objectives in order to constrain the behavior of the learned encoder and de- coder. Experimental results demonstrate that the proposed CD- VAE framework outperforms the conventional VAE framework in terms of subjective tests.Comment: Accepted to ISCSLP 201

IANS: Intelligibility-aware Null-steering Beamforming for Dual-Microphone Arrays

Beamforming techniques are popular in speech-related applications due to their effective spatial filtering capabilities. Nonetheless, conventional beamforming techniques generally depend heavily on either the target's direction-of-arrival (DOA), relative transfer function (RTF) or covariance matrix. This paper presents a new approach, the intelligibility-aware null-steering (IANS) beamforming framework, which uses the STOI-Net intelligibility prediction model to improve speech intelligibility without prior knowledge of the speech signal parameters mentioned earlier. The IANS framework combines a null-steering beamformer (NSBF) to generate a set of beamformed outputs, and STOI-Net, to determine the optimal result. Experimental results indicate that IANS can produce intelligibility-enhanced signals using a small dual-microphone array. The results are comparable to those obtained by null-steering beamformers with given knowledge of DOAs.Comment: Preprint submitted to IEEE MLSP 202

Investigation of degradation caused by charge trapping at etching-stop layer under AC gate-bias stress for InGaZnO thin film transistors

A great amount of literatures has been focusing on bias-induced instability issues including threshold voltage shift (ΔVt ) and subthreshold swing (S.S) degradations [1]. However, in practical TFT operation circuits, very limited knowledge could be applied since operation modes are mostly applied with alternative current (AC). Based on these backgrounds, in this work, Indium-Gallium-Zinc-Oxide Thin Film Transistors (IGZO TFTs) are applied with AC PBS degradations. Compared with previous work, this work observed a structure dependent degradation. An etch-stop structure IGZO TFT observed a serious threshold voltage shift after AC stress but shown great stability after direct current (DC) stress. The device structure and transfer characteristic curves are demonstrated in Figure 1(a) and (b) respectively. From results of DC PBS/NBS, a favorable stability indicating a great quality of gate insulator. Therefore, the positive threshold voltage shift is believed to be origin from electron trapping at the etching stop layer (ESL), since ESL possesses a relatively poor quality compared to the gate insulator. The charge trapping at etching stop layer could be confirmed by results of asymmetric source/drain metal under AC stress, illustrated in Figure 1(c). Please click Additional Files below to see the full abstract

Effect of different a-InGaZnO TFTs channel thickness upon self-heating stress

In this work, Indium-Galium-Zinc-Oxide Thin Film Transistors (IGZO TFTs) with different channel thickness has been compared after self-heating stress (SHS). In previous literatures, self-heating of TFTs has been widely discussed and Joule Heat caused during driving TFTs has been compared with different channel length and width [1]. However, different channel thickness hasn’t been investigated. Although TFTs with a larger channel thickness possess a greater drain current, a less degradation is observed when comparing with small channel thickness structures, demonstrated in Figure 1(a). The ΔVt shift in the transfer characteristics are well described by the stretched-exponential equation. The Eτ value, which is the average effective barrier height for electron transport, is extracted in Figure (b). Results has shown that in the thick IGZO TFTs, the value is almost twice of that in the thin IGZO TFTs. From COMSOL simulations demonstrated in Figure 1(c), in could be noticed that different channel thickness effects the electrical field locating at the gate insulator. Therefore, a model is proposed to explain the degradation difference, illustrated in Figure (4). Please click Additional Files below to see the full abstract