NoreSpeech: Knowledge Distillation based Conditional Diffusion Model for Noise-robust Expressive TTS

Expressive text-to-speech (TTS) can synthesize a new speaking style by imiating prosody and timbre from a reference audio, which faces the following challenges: (1) The highly dynamic prosody information in the reference audio is difficult to extract, especially, when the reference audio contains background noise. (2) The TTS systems should have good generalization for unseen speaking styles. In this paper, we present a \textbf{no}ise-\textbf{r}obust \textbf{e}xpressive TTS model (NoreSpeech), which can robustly transfer speaking style in a noisy reference utterance to synthesized speech. Specifically, our NoreSpeech includes several components: (1) a novel DiffStyle module, which leverages powerful probabilistic denoising diffusion models to learn noise-agnostic speaking style features from a teacher model by knowledge distillation; (2) a VQ-VAE block, which maps the style features into a controllable quantized latent space for improving the generalization of style transfer; and (3) a straight-forward but effective parameter-free text-style alignment module, which enables NoreSpeech to transfer style to a textual input from a length-mismatched reference utterance. Experiments demonstrate that NoreSpeech is more effective than previous expressive TTS models in noise environments. Audio samples and code are available at: \href{http://dongchaoyang.top/NoreSpeech\_demo/}{http://dongchaoyang.top/NoreSpeech\_demo/}Comment: Submitted to ICASSP202

Make-A-Voice: Unified Voice Synthesis With Discrete Representation

Various applications of voice synthesis have been developed independently despite the fact that they generate "voice" as output in common. In addition, the majority of voice synthesis models currently rely on annotated audio data, but it is crucial to scale them to self-supervised datasets in order to effectively capture the wide range of acoustic variations present in human voice, including speaker identity, emotion, and prosody. In this work, we propose Make-A-Voice, a unified framework for synthesizing and manipulating voice signals from discrete representations. Make-A-Voice leverages a "coarse-to-fine" approach to model the human voice, which involves three stages: 1) semantic stage: model high-level transformation between linguistic content and self-supervised semantic tokens, 2) acoustic stage: introduce varying control signals as acoustic conditions for semantic-to-acoustic modeling, and 3) generation stage: synthesize high-fidelity waveforms from acoustic tokens. Make-A-Voice offers notable benefits as a unified voice synthesis framework: 1) Data scalability: the major backbone (i.e., acoustic and generation stage) does not require any annotations, and thus the training data could be scaled up. 2) Controllability and conditioning flexibility: we investigate different conditioning mechanisms and effectively handle three voice synthesis applications, including text-to-speech (TTS), voice conversion (VC), and singing voice synthesis (SVS) by re-synthesizing the discrete voice representations with prompt guidance. Experimental results demonstrate that Make-A-Voice exhibits superior audio quality and style similarity compared with competitive baseline models. Audio samples are available at https://Make-A-Voice.github.i

The relationship between labial soft tissue changes and jumping spaces after immediate implant placement and restoration in the anterior maxilla: A prospective study

Oral implants have been increasingly used in the treatment of edentulous patients or those with dentition defects due to reliable treatment procedure and favorable long-term prognosis. We investigated the changes of labial soft tissue contours with different jumping spaces after immediate implant placement and restoration (IIPR) in the maxillary esthetic area and also provided a long-term stability measurement for the changing trend of soft tissue contour. All patients had been separated into three groups based on the jumping space: group A (horizontal defect dimension [HDD] 2 mm), group B (2 mm 3 mm) and the digital impressions were obtained in the first, third, and sixth month after the operation. The changes of gingival mucosa levels, the average thickness of soft tissue contour volume, and the linear change of submarginal level decreased gradually across the three groups, with the largest change of submarginal level being at 5mm. The size of the jumping space was moderately negatively correlated with the level and average thickness of gingival mucosa and the linear changes of 3 mm and 5 mm under gingival margin, while there was no significant correlation with pink esthetic score (PES) and the linear change of the 1 mm under the gingival margin. Generally, IIPR of upper anterior teeth can achieve esthetic satisfaction, and the level of soft tissue around the implant can be well preserved

Genome-Wide Re-Identification and Analysis of CrRLK1Ls in Tomato

The Catharanthus roseus receptor-like kinase 1-like (CrRLK1L), which is a vital member of the plant receptor-like kinase family, plays versatile roles in plant growth, development, and stress response. Although the primary screening of tomato CrRLK1Ls has been reported previously, our knowledge of these proteins is still scarce. Using the latest genomic data annotations, a genome-wide re-identification and analysis of the CrRLK1Ls in tomatoes were conducted. In this study, 24 CrRLK1L members were identified in tomatoes and researched further. Subsequent gene structures, protein domains, Western blot analyses, and subcellular localization analyses all confirmed the accuracy of the newly identified SlCrRLK1L members. Phylogenetic analyses showed that the identified SlCrRLK1L proteins had homologs in Arabidopsis. Evolutionary analysis indicated that two pairs of the SlCrRLK1L genes had predicted segmental duplication events. Expression profiling analyses demonstrated that the SlCrRLK1L genes were expressed in various tissues, and most of them were up- or down-regulated by bacteria and PAMP treatments. Together, these results will lay the foundation for elaborating the biological roles of SlCrRLK1Ls in tomato growth, development, and stress response

Genome-Wide Re-Identification and Analysis of CrRLK1Ls in Tomato

The Catharanthus roseus receptor-like kinase 1-like (CrRLK1L), which is a vital member of the plant receptor-like kinase family, plays versatile roles in plant growth, development, and stress response. Although the primary screening of tomato CrRLK1Ls has been reported previously, our knowledge of these proteins is still scarce. Using the latest genomic data annotations, a genome-wide re-identification and analysis of the CrRLK1Ls in tomatoes were conducted. In this study, 24 CrRLK1L members were identified in tomatoes and researched further. Subsequent gene structures, protein domains, Western blot analyses, and subcellular localization analyses all confirmed the accuracy of the newly identified SlCrRLK1L members. Phylogenetic analyses showed that the identified SlCrRLK1L proteins had homologs in Arabidopsis. Evolutionary analysis indicated that two pairs of the SlCrRLK1L genes had predicted segmental duplication events. Expression profiling analyses demonstrated that the SlCrRLK1L genes were expressed in various tissues, and most of them were up- or down-regulated by bacteria and PAMP treatments. Together, these results will lay the foundation for elaborating the biological roles of SlCrRLK1Ls in tomato growth, development, and stress response

Unraveling the heterogeneity of cholangiocarcinoma and identifying biomarkers and therapeutic strategies with single-cell sequencing technology

Cholangiocarcinoma (CCA) is a common malignant tumor of the biliary tract that carries a high burden of morbidity and a poor prognosis. Due to the lack of precise diagnostic methods, many patients are often diagnosed at advanced stages of the disease. The current treatment options available are of varying efficacy, underscoring the urgency for the discovery of more effective biomarkers for early diagnosis and improved treatment. Recently, single-cell sequencing (SCS) technology has gained popularity in cancer research. This technology has the ability to analyze tumor tissues at the single-cell level, thus providing insights into the genomics and epigenetics of tumor cells. It also serves as a practical approach to study the mechanisms of cancer progression and to explore therapeutic strategies. In this review, we aim to assess the heterogeneity of CCA using single-cell sequencing technology, with the ultimate goal of identifying possible biomarkers and potential treatment targets

Energy saving and carbon reduction schemes for hospital with photovoltaic power generation and system upgrading technology

In order to help China achieve the double carbon target of total carbon peak and high-quality sustainable economic development, and to enrich the work and content of energy conservation and emission reduction in the building sector, the most complex and energy-consuming hospitals are taken as the key projects for energy conservation and emission reduction to carry out feasibility studies. The reasons for the high energy consumption of the existing hospital buildings were analysed, and it was proposed to upgrade the existing systems (including air conditioning, hot water system and intelligent control system) and to generate photovoltaic power for the existing buildings, taking into account the characteristics of the local climate. The results of the study showed that the energy saving and emission reduction effect of the hospital was obvious after the programme was adopted

Deciphering genetic causality between inflammatory bowel disease and periodontitis through bi-directional two-sample Mendelian randomization

Abstract Inflammatory bowel disease (IBD) and periodontitis are reported to be closely associated; however, whether there is a causal association between them remains unclear. To explore the existence of this causality, this study applied a bidirectional two-sample Mendelian randomization (MR). The genetic variants were obtained from the summary statistics of genome-wide association studies of IBD, including its subtypes CD and UC, and periodontitis. 175, 148, 113, and six single-nucleotide polymorphisms were selected as instrumental variables for IBD, CD, UC, and periodontitis, respectively. In MR analysis, random-effects inverse-variance weighted was used as the primary method, and weighted median and MR Egger regression were applied as the complementary method. A series of sensitivity analyses were also conducted to ensure the reliability of the results. None of these analyses found a significant effect of genetically proxied IBD and its subtypes on periodontitis, and vice versa. Subsequent sensitivity analyses did not detect any horizontal pleiotropy and heterogeneity. Caution should be exerted when it comes to clinical relevance and further studies are needed to clarify the relationship between IBD and periodontitis