190 research outputs found
Robust Disentangled Variational Speech Representation Learning for Zero-shot Voice Conversion
Traditional studies on voice conversion (VC) have made progress with parallel
training data and known speakers. Good voice conversion quality is obtained by
exploring better alignment modules or expressive mapping functions. In this
study, we investigate zero-shot VC from a novel perspective of self-supervised
disentangled speech representation learning. Specifically, we achieve the
disentanglement by balancing the information flow between global speaker
representation and time-varying content representation in a sequential
variational autoencoder (VAE). A zero-shot voice conversion is performed by
feeding an arbitrary speaker embedding and content embeddings to the VAE
decoder. Besides that, an on-the-fly data augmentation training strategy is
applied to make the learned representation noise invariant. On TIMIT and VCTK
datasets, we achieve state-of-the-art performance on both objective evaluation,
i.e., speaker verification (SV) on speaker embedding and content embedding, and
subjective evaluation, i.e., voice naturalness and similarity, and remains to
be robust even with noisy source/target utterances.Comment: Accepted to 2022 ICASS
Activation of protease-activated receptor 2 reduces glioblastoma cell apoptosis
BACKGROUND: The pathogenesis of glioma is unclear. The disturbance of the apoptosis process plays a critical role in glioma growth. Factors regulating the apoptosis process are to be further understood. This study aims to investigate the role of protease activated receptor-2 (PAR2) in regulation the apoptosis process in glioma cells. RESULTS: The results showed that U87 cells and human glioma tissue expressed PAR2. Exposure to tryptase, or the PAR2 active peptide, increased STAT3 phosphorylation in the radiated U87 cells, reduced U87 cell apoptosis, suppressed the expression of p53 in U87 cells. CONCLUSIONS: Activation of PAR2 can reduce the radiated U87 cell apoptosis via modulating the expression of p53. The results implicate that PAR2 may be a novel therapeutic target in the treatment of glioma
Label-free non-invasive subwavelength-resolution imaging using yeast cells as biological lenses
There is a growing interest to use live cells to replace the widely used non-biological microsphere lenses. In this work, we demonstrate the use of yeast cells for such imaging purpose. Using fiber-based optical trapping technique, we trap a chain of three yeast cells and bring them to the vicinity of imaging objects. These yeast cells work as near-field magnifying lenses and simultaneously pick up the sub-diffraction information of the nanoscale objects under each cell and project them into the far-field. The experimental results demonstrated that Blu-ray disc of 100 nm feature can be clearly resolved in a parallel manner by each cell
Unifying Robustness and Fidelity: A Comprehensive Study of Pretrained Generative Methods for Speech Enhancement in Adverse Conditions
Enhancing speech signal quality in adverse acoustic environments is a
persistent challenge in speech processing. Existing deep learning based
enhancement methods often struggle to effectively remove background noise and
reverberation in real-world scenarios, hampering listening experiences. To
address these challenges, we propose a novel approach that uses pre-trained
generative methods to resynthesize clean, anechoic speech from degraded inputs.
This study leverages pre-trained vocoder or codec models to synthesize
high-quality speech while enhancing robustness in challenging scenarios.
Generative methods effectively handle information loss in speech signals,
resulting in regenerated speech that has improved fidelity and reduced
artifacts. By harnessing the capabilities of pre-trained models, we achieve
faithful reproduction of the original speech in adverse conditions.
Experimental evaluations on both simulated datasets and realistic samples
demonstrate the effectiveness and robustness of our proposed methods.
Especially by leveraging codec, we achieve superior subjective scores for both
simulated and realistic recordings. The generated speech exhibits enhanced
audio quality, reduced background noise, and reverberation. Our findings
highlight the potential of pre-trained generative techniques in speech
processing, particularly in scenarios where traditional methods falter. Demos
are available at https://whmrtm.github.io/SoundResynthesis.Comment: Paper in submissio
Seroprevalence and Genetic Characterization of Toxoplasma Gondii in Three Species of Pet Birds in China
Background
Toxoplasmosis, caused by the protozoan parasite Toxoplasma gondii, is one of the most common zoonosis worldwide, affecting a wide range of warm-blooded mammals and birds worldwide. However, no information on T. gondii infection in pet birds in China is available. Therefore, this study was performed to determine the prevalence of T. gondii infection in pet birds in Gansu province, China. Methods
A total of 687 blood samples were collected from pet birds (Carduelis spinus, Alauda gulgula, Cocothraustes migratorlus) in three representative administrative regions in Gansu province, northwest China between August 2011 and September 2012 T. gondii antibodies were determined using the modified agglutination test (MAT). Genomic DNA was extracted from the brain tissues of seropositive pet birds and T. gondii B1 gene was amplified using a semi-nested PCR.DNA samples giving positive B1 amplification were then genetically characterized using multi-locus PCR-RFLP. Results
The overall T. gondii seroprevalence was 11.21% (77/687). C. spinus had the highest T. gondii seroprevalence (11.65%), followed by A. arvensis (11.39%) and C. migratorlus (5.26%), these differences were not statistically significant (P \u3e 0.05). Of 77 DNA samples, 8 were positive for the T. gondii B1 gene, four showed complete genotyping results. Only one genotype (the Type II variant: ToxoDB genotype #3) was identified. Conclusions
The results of the present survey indicated the presence of T. gondii infection in pet birds in Gansu province, China. These data provide base-line information for the execution of control strategies against T. gondii infection in pet birds. To our knowledge, this is the first report documenting the occurrence of T. gondii prevalence and genotype in pet birds in China
Flexible Micro-Nano Fiber Sensors for Tactile Sensing
Flexible tactile sensors play an important role in wearable devices, human–computer interaction devices, and advanced robotics. We propose a novel structure of bionic flexible tactile sensor. The micro-nano fibers (MNFs) are packed in a 10-μm film on a polydimethylsiloxane (PDMS) base, forming a thin film-MNF-PDMS structure. A ridge-shaped sensing region is formed on the surface of the PDMS substrate. The MNF is so close to the sensor surface that vibration and pressure signals can act directly on the MNF. Compared to existing MNF flexible sensors, this sensor has higher sensitivity and faster response time. We tested the response of the flexible sensor to vibration and temperature. This sensor can measure vibration signals from 0.1 Hz to2 kHz. The sensitivity of this sensor to temperature can reach 1.43 nm/◦C. Surfaces with different roughness or texture can be distinguished by sliding on the sensor surface. The structural and functional characteristics of this sensor are desirable in flexible bionic devices and advanced robots
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