An ASR-free Fluency Scoring Approach with Self-Supervised Learning

A typical fluency scoring system generally relies on an automatic speech recognition (ASR) system to obtain time stamps in input speech for either the subsequent calculation of fluency-related features or directly modeling speech fluency with an end-to-end approach. This paper describes a novel ASR-free approach for automatic fluency assessment using self-supervised learning (SSL). Specifically, wav2vec2.0 is used to extract frame-level speech features, followed by K-means clustering to assign a pseudo label (cluster index) to each frame. A BLSTM-based model is trained to predict an utterance-level fluency score from frame-level SSL features and the corresponding cluster indexes. Neither speech transcription nor time stamp information is required in the proposed system. It is ASR-free and can potentially avoid the ASR errors effect in practice. Experimental results carried out on non-native English databases show that the proposed approach significantly improves the performance in the "open response" scenario as compared to previous methods and matches the recently reported performance in the "read aloud" scenario.Comment: Accepted by ICASSP 202

Leveraging phone-level linguistic-acoustic similarity for utterance-level pronunciation scoring

Recent studies on pronunciation scoring have explored the effect of introducing phone embeddings as reference pronunciation, but mostly in an implicit manner, i.e., addition or concatenation of reference phone embedding and actual pronunciation of the target phone as the phone-level pronunciation quality representation. In this paper, we propose to use linguistic-acoustic similarity to explicitly measure the deviation of non-native production from its native reference for pronunciation assessment. Specifically, the deviation is first estimated by the cosine similarity between reference phone embedding and corresponding acoustic embedding. Next, a phone-level Goodness of pronunciation (GOP) pre-training stage is introduced to guide this similarity-based learning for better initialization of the aforementioned two embeddings. Finally, a transformer-based hierarchical pronunciation scorer is used to map a sequence of phone embeddings, acoustic embeddings along with their similarity measures to predict the final utterance-level score. Experimental results on the non-native databases suggest that the proposed system significantly outperforms the baselines, where the acoustic and phone embeddings are simply added or concatenated. A further examination shows that the phone embeddings learned in the proposed approach are able to capture linguistic-acoustic attributes of native pronunciation as reference.Comment: Accepted by ICASSP 202

Communication-efficient three-party protocols for authentication and key agreement

AbstractEncrypted key exchange (EKE) authentication approaches are very important for secure communicating over public networks. In order to solve the security weaknesses three-party EKE, Yeh et al. [H.T. Yeh, H.M. Sun, T. Hwang, Efficient three-party authentication and key agreement protocols resistant to password guessing attacks, Information Science and Engineering 19 (6) (2003) 1059–1070.] proposed two secure and efficient three-party EKE protocols. Based on the protocol developed by Yeh et al., two improved EKE protocols for authentication and key agreement are proposed in this study. The computational costs of the proposed protocols are the same as those of the protocols of Yeh et al. However, the numbers of messages in the communication are fewer than those of the protocols of Yeh et al. Furthermore, the round efficient versions of our proposed protocols are also described

Starless Cloud Core L1517B in Envelope Expansion with Core Collapse

Various spectral emission lines from star-forming molecular cloud core L1517B manifest red asymmetric double-peaked profiles with stronger red peaks and weaker blue peaks, in contrast to the oft-observed blue-skewed molecular spectral line profiles with blue peaks stronger than red peaks. Invoking a spherically symmetric general polytropic hydrodynamic shock model for the envelope expansion with core collapse (EECC) phase, we show the radial flow velocity, mass density and temperature structures of self-similar evolution for L1517B in a dynamically consistent manner. By prescribing simple radial profiles of abundance distribution for pertinent molecules, we perform molecular excitation and radiative transfer calculations using the publicly available RATRAN code set for the spherically symmetric case. Our computational results show that the EECC model reproduces molecular spectral line profiles in sensible agreement with observational data of IRAM, FCRAO and Effelsberg 100 m telescopes for L1517B. We also report spatially resolved observations of optically thick line HCO+(1-0) using the Purple Mountain Observatory (PMO) 13.7 m telescope at Delingha in China and the relevant fitting results. Hyperfine line structures of NH3 and N2H+ transitions are also fitted to consistently reveal the dynamics of central core collapse. As a consistent model check, radial profiles of 1.2 mm and 0.85 mm dust continua observed by IRAM 30 m telescope and SCUBA, respectively, are also fitted numerically using the same EECC model that produces the molecular line profiles. L1517B is likely undergoing an EECC shock phase. For future observational tests, we also predict several molecular line profiles with spatial distributions, radial profile of sub-millimeter continuum at wavelength 0.45mm, as well as the radial profiles of the column density and visual extinction for L1517B.Comment: 18 pages, 11 figures, accepted for publication in Ap

High-performance biosensing systems based on various nanomaterials as signal transducers

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Direct evidence of ZnO morphology modification via the selective adsorption of ZnO-binding peptides

Biomolecule-mediated ZnO synthesis has great potential for the tailoring of ZnO morphology for specific application in biosensors, window materials for display and solar cells, dye-sensitized solar cells (DSSCs), biomedical materials, and photocatalysts due to its specificity and multi-functionality. In this contribution, the effect of a ZnO-binding peptide (ZnO-BP, G-12: GLHVMHKVAPPR) and its GGGC-tagged derivative (GT-16: GLHVMHKVAPPRGGGC) on the growth of ZnO crystals expressing morphologies dependent on the relative growth rates of (0001) and (10 (1) over bar0) planes of ZnO have been studied. The amount of peptide adsorbed was determined by a depletion method using oriented ZnO films grown by Atomic Layer Deposition (ALD), while the adsorption behavior of G-12 and GT-16 was investigated using XPS and a computational approach. Direct evidence was obtained to show that (i) both the ZnO-BP identified by phage display and its GGGC derivative (GT-16) are able to bind to ZnO and modify crystal growth in a molecule and concentration dependent fashion, (ii) plane selectivity for interaction with the (0001) versus the (10 (1) over bar0) crystal planes is greater for GT-16 than G-12; and (iii) specific peptide residues interact with the crystal surface albeit in the presence of charge compensating anions. To our knowledge, this is the first study to provide unambiguous and direct quantitative experimental evidence of the modification of ZnO morphology via (selective and nonselective) adsorption-growth inhibition mechanisms mediated by a ZnO-BP identified from phage display libraries

Advances in Microfluidics and Lab-on-a-Chip Technologies

Advances in molecular biology are enabling rapid and efficient analyses for effective intervention in domains such as biology research, infectious disease management, food safety, and biodefense. The emergence of microfluidics and nanotechnologies has enabled both new capabilities and instrument sizes practical for point-of-care. It has also introduced new functionality, enhanced sensitivity, and reduced the time and cost involved in conventional molecular diagnostic techniques. This chapter reviews the application of microfluidics for molecular diagnostics methods such as nucleic acid amplification, next-generation sequencing, high resolution melting analysis, cytogenetics, protein detection and analysis, and cell sorting. We also review microfluidic sample preparation platforms applied to molecular diagnostics and targeted to sample-in, answer-out capabilities

Longer telomere length in peripheral white blood cells is associated with risk of lung cancer and the rs2736100 (CLPTM1L-TERT) polymorphism in a prospective cohort study among women in China.

A recent genome-wide association study of lung cancer among never-smoking females in Asia demonstrated that the rs2736100 polymorphism in the TERT-CLPTM1L locus on chromosome 5p15.33 was strongly and significantly associated with risk of adenocarcinoma of the lung. The telomerase gene TERT is a reverse transcriptase that is critical for telomere replication and stabilization by controlling telomere length. We previously found that longer telomere length measured in peripheral white blood cell DNA was associated with increased risk of lung cancer in a prospective cohort study of smoking males in Finland. To follow up on this finding, we carried out a nested case-control study of 215 female lung cancer cases and 215 female controls, 94% of whom were never-smokers, in the prospective Shanghai Women's Health Study cohort. There was a dose-response relationship between tertiles of telomere length and risk of lung cancer (odds ratio (OR), 95% confidence interval [CI]: 1.0, 1.4 [0.8-2.5], and 2.2 [1.2-4.0], respectively; P trend = 0.003). Further, the association was unchanged by the length of time from blood collection to case diagnosis. In addition, the rs2736100 G allele, which we previously have shown to be associated with risk of lung cancer in this cohort, was significantly associated with longer telomere length in these same study subjects (P trend = 0.030). Our findings suggest that individuals with longer telomere length in peripheral white blood cells may have an increased risk of lung cancer, but require replication in additional prospective cohorts and populations

Interferometric Fiber Optic Sensors

Fiber optic interferometers to sense various physical parameters including temperature, strain, pressure, and refractive index have been widely investigated. They can be categorized into four types: Fabry-Perot, Mach-Zehnder, Michelson, and Sagnac. In this paper, each type of interferometric sensor is reviewed in terms of operating principles, fabrication methods, and application fields. Some specific examples of recently reported interferometeric sensor technologies are presented in detail to show their large potential in practical applications. Some of the simple to fabricate but exceedingly effective Fabry-Perot interferometers, implemented in both extrinsic and intrinsic structures, are discussed. Also, a wide variety of Mach-Zehnder and Michelson interferometric sensors based on photonic crystal fibers are introduced along with their remarkable sensing performances. Finally, the simultaneous multi-parameter sensing capability of a pair of long period fiber grating (LPG) is presented in two types of structures; one is the Mach-Zehnder interferometer formed in a double cladding fiber and the other is the highly sensitive Sagnac interferometer cascaded with an LPG pair