SingVisio: Visual Analytics of Diffusion Model for Singing Voice Conversion

In this study, we present SingVisio, an interactive visual analysis system that aims to explain the diffusion model used in singing voice conversion. SingVisio provides a visual display of the generation process in diffusion models, showcasing the step-by-step denoising of the noisy spectrum and its transformation into a clean spectrum that captures the desired singer's timbre. The system also facilitates side-by-side comparisons of different conditions, such as source content, melody, and target timbre, highlighting the impact of these conditions on the diffusion generation process and resulting conversions. Through comprehensive evaluations, SingVisio demonstrates its effectiveness in terms of system design, functionality, explainability, and user-friendliness. It offers users of various backgrounds valuable learning experiences and insights into the diffusion model for singing voice conversion

Emilia: An Extensive, Multilingual, and Diverse Speech Dataset for Large-Scale Speech Generation

Recent advancements in speech generation models have been significantly driven by the use of large-scale training data. However, producing highly spontaneous, human-like speech remains a challenge due to the scarcity of large, diverse, and spontaneous speech datasets. In response, we introduce Emilia, the first large-scale, multilingual, and diverse speech generation dataset. Emilia starts with over 101k hours of speech across six languages, covering a wide range of speaking styles to enable more natural and spontaneous speech generation. To facilitate the scale-up of Emilia, we also present Emilia-Pipe, the first open-source preprocessing pipeline designed to efficiently transform raw, in-the-wild speech data into high-quality training data with speech annotations. Experimental results demonstrate the effectiveness of both Emilia and Emilia-Pipe. Demos are available at: https://emilia-dataset.github.io/Emilia-Demo-Page/.Accepted in SLT 2024. Dataset available: https://huggingface.co/datasets/amphion/Emilia-Datase

FuzzCoder: Byte-level Fuzzing Test via Large Language Model

Fuzzing is an important dynamic program analysis technique designed for finding vulnerabilities in complex software. Fuzzing involves presenting a target program with crafted malicious input to cause crashes, buffer overflows, memory errors, and exceptions. Crafting malicious inputs in an efficient manner is a difficult open problem and the best approaches often apply uniform random mutations to pre-existing valid inputs. In this work, we propose to adopt fine-tuned large language models (FuzzCoder) to learn patterns in the input files from successful attacks to guide future fuzzing explorations. Specifically, we develop a framework to leverage the code LLMs to guide the mutation process of inputs in fuzzing. The mutation process is formulated as the sequence-to-sequence modeling, where LLM receives a sequence of bytes and then outputs the mutated byte sequence. FuzzCoder is fine-tuned on the created instruction dataset (Fuzz-Instruct), where the successful fuzzing history is collected from the heuristic fuzzing tool. FuzzCoder can predict mutation locations and strategies locations in input files to trigger abnormal behaviors of the program. Experimental results show that FuzzCoder based on AFL (American Fuzzy Lop) gain significant improvements in terms of effective proportion of mutation (EPM) and number of crashes (NC) for various input formats including ELF, JPG, MP3, and XML.11 page

Travel Experience creation in the context of mobile technologies

Through the use of self-service mobile device, the traditional marketspace interaction is being replaced by a marketspace transaction, where the foundation of customer-company interaction has significantly changed. They will require us to rethink the core assumptions of customer experience, such as service clues, relationship management and value creation. To accommodate these characteristics, we must rethink the customer experience creation perspectives (e.g., from management dominant to customer dominant view of thinking). Meanwhile, we must rethink issues of the scope of customer experience (e.g. from core service to overall customer context) and temporal scope of customer experience (e.g. from service encounter to life-long customer experience).</p

The Role of Self-Service Mobile Technologies in the Creation of Customer travel Experiences

Through the use of self-service mobile devices, the traditional marketplace interaction is being replaced by a marketspace transaction, in which the foundation of customer-company interaction has changed. This article discusses the main actors of experiencial value creation through the physical world and virtual world in the context of transport service. The empirical data is collected from semi-structured interviews with 19 young urban transport commuters. The results show that self-service mobile devices enhance the information accessibility for passengers to create customized travel experiences through a closer interaction with other actors, including transport service providers, transport-related service providers, and other passengers. Moreover, the scope of travel experience was expanded beyond the traditional service encounter both temporally and spatially. This article is an exploration of the influence of self-service mobile devices in the changing roles of customers and companies. A key message is that executives must pay attention to how their companies create experience value in both the physical world and the virtual world, separately or in combination.</p

Improved Empirical Wavelet Transform for Compound Weak Bearing Fault Diagnosis with Acoustic Signals

Most of the current research on the diagnosis of rolling bearing faults is based on vibration signals. However, the location and number of sensors are often limited in some special cases. Thus, a small number of non-contact microphone sensors are a suboptimal choice, but it will result in some problems, e.g., underdetermined compound fault detection from a low signal-to-noise ratio (SNR) acoustic signal. Empirical wavelet transform (EWT) is a signal processing algorithm that has a dimension-increasing characteristic, and is beneficial for solving the underdetermined problem with few microphone sensors. However, there remain some critical problems to be solved for EWT, especially the determination of signal mode numbers, high-frequency modulation and boundary detection. To solve these problems, this paper proposes an improved empirical wavelet transform strategy for compound weak bearing fault diagnosis with acoustic signals. First, a novel envelope demodulation-based EWT (DEWT) is developed to overcome the high frequency modulation, based on which a source number estimation method with singular value decomposition (SVD) is then presented for the extraction of the correct boundary from a low SNR acoustic signal. Finally, the new fault diagnosis scheme that utilizes DEWT and SVD is compared with traditional methods, and the advantages of the proposed method in weak bearing compound fault diagnosis with a single-channel, low SNR, variable speed acoustic signal, are verified.</jats:p

Thiol-Catalyzed Photodriven Stereoselective Hydrodifluoroacetylative Cyclization of Alkyne

A metal-free protocol for visible-light-driven intramolecular hydrodifluoroacetylative cyclization of N-propargyl or N-homopropargyl-2-bromo-2,2-difluoroacetamide to α,α-difluorinated β-substituted γ- or δ-lactam without an additional photosensitizer has been developed. By using thiol and Hantzsch ester as the catalyst and hydrogen donor, respectively, to implement a hydrogen atom transfer process, moderate to high (Z) selectivity was achieved. The results of a mechanistic investigation revealed the critical contribution of the thiol catalyst in attaining the stereoselectivity

Ni-Catalyzed enantioselective reductive arylcyanation/cyclization of <i>N</i>-(2-iodo-aryl) acrylamide

A Ni/(S,S)-BDPP-catalyzed intramolecular Heck cyclization of N-(2-iodo-aryl) acrylamide with 2-methyl-2-phenylmalononitrile was developed to give oxindoles with good enantioselectivities.</jats:p

Ligand-Controlled Regiodivergent Alkoxycarbonylation of Trifluoromethylthiolated Internal Alkynes

Controlling the regioselectivity for the alkoxycarbonylation of unsymmetric internal alkynes is challenging. Herein, a palladium-catalyzed ligand-controlled regiodivergent alkoxycarbonylation of internal trifluoromethylthiolated alkynes was achieved. A series of α- or β-SCF3 acrylates from the same trifluoromethylthiolated alkyne were obtained with moderate to high yield and regioselectivity

Meta-Analysis of Daoyin Therapy on Therapeutic Effect and Quality of Life in Patients with Stable Angina Pectoris

ObjectiveTo evaluate the therapeutic effect and quality of life of Daoyin therapy in the treatment of stable angina pectoris of coronary heart disease.MethodsEight databases, including CNKI, VIP, Wanfang, SinoMed, PubMed, Cochrane Library, Embase, and Web of Science were searched through the computer retrieval system, and the RCTs of Daoyin therapy for stable angina pectoris were screened. The retrieval time was from inception to December 2021.The risk of bias assessment tool provided by the Cochrane Reviewers Handbook 5.1 was used to assess the quality of the literature, and the RevMan 5.3 software (provided by the Cochrane Collaboration) was used to perform a meta-analysis. Primary outcomes included the number of angina attacks, the angina duration and Seattle angina questionnaire (SAQ) scores. Secondary outcomes included Self-Rating Anxiety Scale (SAS) scores, Self-Rating Depression Scale (SDS) scores, 6-minutes walk test (6MWT) and Metabolic Equivalents (METs）. Continuous variables were expressed by Mean Difference (MD) and 95% confidence interval (CI). If the included studies were homogeneous (P&gt;0.1, I2≤50%), a fixed effects model would be used; if the included studies were heterogeneous (P≤0.1, I2&gt;50%), a random-effects model would be used.ResultsA total of 15 RCTs were included, involving 1 261 cases, with 631 in the Daoyin group and 630 in the control group. The overall quality of the included studies was not high. Meta-analysis showed that compared with the control group, Daoyin therapy can significantly reduce the number of angina pectoris attacks [MD=-1.70, 95%CI (-2.07, -1.34), P&lt;0.000 01], shorten the duration of angina pectoris [MD=-1.17, 95%CI (-1.38, -0.96), P&lt;0.000 01], reduce SAS scores [MD=-4.71, 95%CI (-7.12, -2.31), P=0.000 1] and SDS scores [MD=-3.91, 95%CI (-5.75, -2.07), P&lt;0.000 1], and improve METs [MD=1.20, 95%CI (0.39, 2.01), P=0.004] and SAQ scores [MD=7.62, 95%CI (5.97, 9.27), P&lt;0.000 01]; Taijiquan [MD=39.52, 95%CI (19.30, 59.74), P=0.000 1] and Shaolin Neigong (P&lt;0.000 1) can improve 6MWT, while Baduanjin [MD=1.39, 95%CI (-9.13, 11.92), P=0.80] and Yixincao (P=0.30) have no statistical difference in improving 6MWT.ConclusionDaoyin therapy is effective to treat patients with stable angina pectoris of coronary heart disease by improving clinical efficacy, alleviating depression and anxiety symptoms and improving quality of life when applied alone or as an add-on measure to the conventional therapy/exercise