Reviewerly/exHarmony huggingface dataset:
Transcribing and Aligning Conversational Speech: A Hybrid Pipeline Applied to French Conversations

With the advent of transformer based models, the use of fully automated ASR-pipelines in a real-world context has come close to a reality. However, for faithful transcription of conversational speech, there remain challenges both in terms of the content predicted by these models (hallucinations, unintended normalizations of disfluencies and transcriptions of background noises) and in terms of alignment accuracy. In this paper we present a hybrid ASR-pipeline which augments transformer models with other algorithms in order to transcribe conversational data. Through experiments on two French datasets, we show that: 1) VAD preprocessing can significantly improve transcription quality as well as word level temporal alignment, 2) prompting can reduce unintended normalizations of disfluencies, 3) heuristic-based detection of untranscribed sounds can further improve alignment quality. We conclude that our hybrid pipeline is an efficient way to improve and augment existing ASR-models.
Semi-Supervised Multi-Channel Speaker Diarization With Cross-Channel Attention

Most neural speaker diarization systems rely on sufficient manual training data labels, which are hard to collect under real-world scenarios. This paper proposes a semi-supervised speaker diarization system to utilize large-scale multi-channel training data by generating pseudo-labels for unlabeled data. Furthermore, we introduce cross-channel attention into the Neural Speaker Diarization Using Memory-Aware Multi-Speaker Embedding (NSD-MA-MSE) to learn channel contextual information of speaker embeddings better. Experimental results on the CHiME-7 Mixer6 dataset which only contains partial speakers’ labels of the training set, show that our system achieved 57.01% relative DER reduction compared to the clustering-based model on the development set. We further conducted experiments on the CHiME- 6 dataset to simulate the scenario of missing partial training set labels. When using 80% and 50% labeled training data, our system performs comparably to the results obtained using 100% labeled data for training.
Exploring the Viability of Synthetic Audio Data for Audio-Based Dialogue State Tracking

Dialogue state tracking plays a crucial role in extracting information in task-oriented dialogue systems. However, preceding research are limited to textual modalities, primarily due to the shortage of authentic human audio datasets. We address this by investigating synthetic audio data for audio-based DST. To this end, we develop cascading and end-to-end models, train them with our synthetic audio dataset, and test them on actual human speech data. To facilitate evaluation tailored to audio modalities, we introduce a novel PhonemeF1 to capture pronunciation similarity. Experimental results showed that models trained solely on synthetic datasets can generalize their performance to human voice data. By eliminating the dependency on human speech data collection, these insights pave the way for significant practical advancements in audio-based DST. Data and code are available at https://github.com/JihyunLee1/E2E-DST. <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">1</sup>
Research on the enhancement path of talent cultivation in the integration of dual-creation education and professional education for teacher training majors in colleges and universities based on multivariate statistical analysis

Abstract In today’s society, under the demand for high-quality talents, the professionals cultivated in colleges and universities should not only master professional skills but also need to have the spirit of innovation and entrepreneurial ability in professional aspects. In this paper, firstly, the multivariate statistical analysis method is explained, and the basic principles of the factor analysis model, principal component analysis method and systematic clustering method are given to analyze the data in the following article. Secondly, starting from the necessity of the integration of bi-initiative education and professional education of teacher training majors in colleges and universities, we constructed the 4344 specialized and innovative integrated talent cultivation model of teacher training majors and constructed an evaluation system to evaluate the effectiveness. Finally, based on the evaluation system, the data analysis of the specialized and creative integrated talent cultivation model was carried out using factor analysis, principal component analysis and systematic clustering method. The results show that in the factor analysis, the highest loading value of the first principal factor is 0.917, the contribution rate of the first principal factor is 39.67%, and the loading value of the principal component factor reaches the highest value of 0.925. The clustering analysis is based on the results of the factor analysis, and the respondents are divided into 4 clusters. The number of people in the 2nd category is more than 30 people, which accounts for about 31.41% of the total number of people. The method of multivariate statistical analysis can be used to analyze the data effectively for the specialized and integrated personnel training mode of teacher training in colleges and universities and also gives the path of specialized and integrated personnel training for teacher training.
The Correlation Between Students’ Visual Learning Style Preference and Vocabulary Mastery at SMP NEGERI 3 Sungguminasa

The objective of this research is to find out the correlation between students' visual learning style preference and vocabulary mastery at SMP Negeri 3 Sungguminasa. The design of this research is descriptive quantitative research. This research has two variables, students' visual learning style preference as an independent variable and students’ vocabulary mastery as a dependent variable. The population of this research is seventh-grade students. The researcher used random sampling to take the samples, which consist of 33 students. In collecting the data, the researcher used a questionnaire and test. The questionnaire used to measure students’ visual learning style preference, which consists of 15 statements. Then, the test is used to know students’ vocabulary mastery which consists of 20 questions. In analyzing the data, the researcher used Pearson analyzed Product Moment Correlation formula. The data analyzed by using SPSS 23 program for Windows. The result of this research shows that there was a medium correlation between students’ visual learning style preference and vocabulary mastery of VII grade students of SMP Negeri 3 Sungguminasa because the value of rxy = 0.468 on the correlation scale table (0.40-0.599) means in medium correlation level. As the findings showed, rxy &gt; rtable = 0.468 &gt;0.40 So, it can be concluded that there was a significant correlation between students’ visual learning style and vocabulary mastery at SMP Negerei 3 Sungguminasa
ChatGeppetto - an AI-powered Storyteller

In this paper we introduce a novel highly interactive process to generate natural language narratives on the basis of our ongoing work on semiotic relations. To the two basic components of interactive systems, namely, a software tool and a user interface, we add a third component – AI agents, understood as an upgraded rendition of software agents. Our semiotic relations approach considers four ways of composing new narratives from existing narratives. Along what semioticians call the horizontal syntagmatic axis, one can form the new narrative by combining two or more previous narratives. Along the vertical paradigmatic axis, the new narrative may emerge as a similar version, which imitates the previous one, possibly in a different context. Along the depth meronymic axis, the hierarchic narrative levels, such as plot, event, and scene, are explored, allowing either expansion or summarization. Lastly, the antithetic consideration, rather than adding a dimension, aims at some form of reversal, through the adoption of opposite values. A fully operational prototype is described. Its name, ChatGeppetto, conflates the skilled Geppetto, who fashioned Pinocchio, an early case of artisanship-produced human level intelligence, with ChatGPT, which operates as the main AI agent component. To run the experiments, we concentrated on book narratives.
ABILITY INTEGRATE DIGITAL TECHNOLOGY BY HEALTH PROFESIONALS DURING THE TEAHING AND LEARNING PROCES IN THE ERA OF GLOBALIZATION: A INTEGRATED RIVIEW

In the era of the industrial 4.0, there is an increase in the availability of portable digital technology equipment that supports the learning process in various sectors including health. It is become a core requirement to support the learning process. Digital technology application media such as You Tube, Google Apps, Zoom, Face books, Skype, Dropbox, twitter, WhatsApp and others have become core health learning tools today. The readiness of health workers to utilize digital applications in the learning process, so in needs to be considered. The aims of this study was to explore the readiness of health professional in using digital technology to facilitate the teaching and learning process. Mechanism of goal attainment in this study using the five measures of Whitmore and Knafl. Researcher searched for articles through the google scholar, ProQuest and Science Direct. Article search of January to August 2022 publication period have concentrated of the health professional use technology digital to facelifted their learning. Was used PRISMA checklist with key word: Ability AND health AND Integration AND digital AND Learning. Was choose a cross sectional study for this study. The total 15 articles selected and included in this study with JBI analysis value is at least 88,5%. The use of digital technology in the learning process in the health sector has proven to be very effective and efficient.
WAYS TO FORM THE BASIS OF MEDIA LITERACY IN PRIMARY SCHOOL STUDENTS DURING COMPUTER SCIENCE CLASS

The article justifies theoretically the ways of forming the basics of media literacy in primary school students at the computer science lessons. It has been determined that the following ways contribute to the formation of media literacy: the conducting of a system of computer science lessons using specific forms, methods and techniques of work, filled with the purposeful motivated media-active performance of the students; the analysis and integration of media products (the development of critical thinking); the involvement in media creativity. Each of the named ways is self-sufficient, but when implemented in a system, they become multi-vector under the influence of external and internal factors. It is important that by developing certain skills in different situations, an individual acquires media literacy, which helps form their own identity and independence. One of the defining ways of forming the basics of media literacy at the computer science lessons is the use of various pedagogical forms, methods, and work techniques that contribute to the purposeful motivated media-active performance of the students. Another effective way is the analysis and the integration of media resources. In this regard, primary school computer science lessons should develop the skills for safe interaction with television, the Internet, and other media, in order neither to abuse nor to harm their own development and psychological health. Computer science lessons should contribute to the increase of the students' resilience to information manipulation and propaganda, as well as to prevent abuse and the destructive influence of the media on children's psyche. Based on the above, it has been established that the formation of the basics of media literacy in primary school students is promoted by: the conducting of a system of computer science lessons with the use of specific forms, methods, and techniques of work, filled with the purposeful motivated media-active performance of the students; the analysis and integration of media products (the development of critical thinking); the involvement in media creativity.&#x0D; Keywords: information; media; media illiteracy; media education; primary school students; computer science lessons; computer; methods; techniques; forms; ways.
Research on the Application and Effect of Innovative Teaching Methods in College Student Education

With the rapid development of society and the rapid updating of knowledge, traditional teaching models can no longer meet the needs of college students. Therefore, this study aims to explore the application and effectiveness of innovative teaching methods in college student education. Research has shown that innovative teaching methods can stimulate students' active learning ability, cultivate innovative thinking and problem-solving abilities, and have a positive impact on their development. This study proposes implementation strategies and suggestions for innovative teaching methods in university education, and the implementation strategies for innovative teaching methods in university student education provide reference for university teachers and education managers.
Transistors: The Building Blocks of Computers!

In this chapter, we’ll learn how to use transistors to switch and amplify electrical signals. We’ll also learn the basics of how transistors work, and we’ll dig into how transistors transformed electronics to enable modern computers, hooray!
A Brief Analysis of the Application of Catford’s Translation Shifts to English for Communication Technology Translation into Chinese

Translation shift theory; Communication technical English; Translation study
A Study of College English Vocabulary Teaching from the Perspective of Semantic Field

Semantic field; College English vocabulary; Teaching model
The Challenges of CEFR adoption: Teachers’ understanding and classroom practice

CEFR has been extensively adopted in many countries including Malaysia. Currently at the third phase of the implementation, the concept of CEFR and the applicability is not new to most teachers. Over the years, numerous local studies have been conducted to discover the real situation faced by both teachers and students who are directly affected by the government’s decision to replace the previous syllabus with the new CEFR aligned English syllabus. This study was conducted with the objectives of investigating the challenges encountered by English teachers on understanding CEFR and the potential challenges faced by the teachers in CEFR classroom practice in the adoption process. A panel member of the English Language Standard and Quality Council (ELSQC) and 331 school teachers participated in this study. Survey and in-depth interview were employed for data gathering. Computer software such as NVivo and SPSS were used for data analysis. Results show that most teachers lack understanding especially on the adoption of the framework. Moreover, classroom practice is a real challenge to the teachers because the imported CEFR-aligned textbooks are causing additional workload due to adapt them to the local context. Preparing and designing their own CEFR aligned teaching materials based on the new syllabus is another challenge of classroom practice for the teachers.
The Exploration of Live Broadcast Teaching (1): Questions and Difficulties

Live broadcast; Questions; Difficulties
A Study on the Relationship between “Coterie Journals” and Societybased Literary Schools: A Case Study of The Crescent Moon

“Coterie Journals”; The Crescent Moon monthly magazine; Society-based literary schools
Many-objective particle swarm optimisation algorithm based on multi-elite opposition mutation mechanism in the internet of things environment

Multi-objective optimisation problem in Internet of Things technology has been widely concerned by researchers. The family of multi-objective particle swarm optimisation is among the most representative ones. However, there still exist the shortcomings of overspending and premature convergence. This paper proposes a many-objective particle swarm optimisation algorithm based on opposition-based mutation for elite mechanism. The new algorithm mainly includes three strategies: (1) Opposition-based learning population initialisation strategy, which is designed to avoid the blindness and uncertainty of initial population, and improves the distribution of population and accelerates speed of exploration. (2) Multi-elite opposition mutation mechanism, which is proposed to help particles get away from local optimal positions via a targeted exploration in the search space. (3) Singularity archive technique, which is established to disturb the global evolution trend and further balance the contradiction of convergence and diversity of the population. The effectiveness of the proposed algorithm is verified by comparing 11 algorithms in the simulation experiments.
Keyword extraction from news corpus by deep learning in the context of internet of things

With the rapid development of modern technology and information technology, information generation and dissemination is getting faster and faster. The amount of web text, such as web pages, e-books, news, etc., is exploding. Therefore, it is very important for users to quickly and accurately find out what they are interested in from the large amount of data in the network. Keywords can help users quickly understand the main content of the text and the main idea, improve query efficiency, and save search time. Therefore, in order to solve the problem of increasing information volume, searching for the information people need more efficiently, exploring new technologies for keyword extraction, and improving the accuracy of keyword extraction are more and more important.
Security technology for data transmission to the internet of things devices under the application of blockchain technology

The objectives of this work are to improve the security of citizen identity verification, and data privacy in the network environment, to solve the problems of low security in the process of network information transmission when privacy cannot be reasonably maintained. It aims to further optimise the environment for network information transmission, improve the security and concealment in the process of information transmission and enhance the expansion and application of blockchain technology in the field of network security, thus providing a strong technical guarantee for information transmission, making it safer and more reliable in practice. An authentication transmission system for general data of the Internet of Things (IoT) based on the application of blockchain technology is proposed. In this process, the Gossip consensus algorithm is innovatively integrated into the data transmission process.
Research on the Development and Utilization of Learning Resources in Network Courses

Online courses; Learning resources; Development; Utilize
The Application and Practice of Digital Transformation in College English Reform

College English; Higher education reform; Digital transformation
Radicalism Is Not Extremism

This chapter discusses successful propaganda campaigns being finely attuned to the United State's culture and practices, especially with how the audiences use technology to find information. Meaning-making practices are not only strictly used by conservative pundits and politicians. However, conservative elites fear that social movements designed to improve access and inclusion will hamper their ability to maintain power. The chapter also looks into the concept of the Overton Window, which is used for mapping the range of ideas that the public discourse can tolerate. Since media manipulation practices constantly evolve, exposing the scheme behind the practice may result in the advocacy of greater transparency and verification.
The Primitive Today

Chapter 5 accounts for the complex primitivism of Henry David Thoreau’s writings, under the phenomenological influence of figures like Emerson and Goethe, but also of a wide range of contributors to the linguistic study of Indigenous American languages, such as Heckewelder, Du Ponceau, and Schoolcraft. The chapter examines Thoreau’s desire for proximity to Wabanaki languages of the Northeast, like Penobscot, alongside his inability to understand them as contemporary with his own utterance. It locates the contradictions that stem from the persistence of Thoreau’s racialized primitivism with respect to Indigenous life, in the face of his meticulous work with etymological tropes against origins-thinking and his regard for variation, mixed durations, and regeneration in the natural world. Among other texts, the chapter examines The Maine Woods, Walden, the Journal, and the unpublished Indian Notebooks.
Wavelength-Parallel Photonic Tensor Core Based on Multi-FSR Microring Resonator Crossbar Array

This paper proposes a wavelength-parallel photonic tensor core by exploiting multiple free spectral ranges (multi-FSRs) of the microring resonator crossbar array architecture. As an example, a four-FSR 4×4 crossbar array is designed and simulated.
Controllable Passive Multi-polarization-states Generator based on Silicon Photonics for Quantum Communication

We demonstrate a silicon-based controllable multi-polarization-states generator for quantum key distribution. Our device can effectively generate various sets of well-defined four-polarization states using the thermo-optics effect and combine them into one port at a telecom-wavelength.
Demonstration of Reference Frame Independent Quantum Key Distribution with Integrated Optical Circuits

Free-space quantum key distribution usually requires limited space and weight. We implement reference frame independent quantum key distribution protocol with chip-scale integrated optical circuits such as laser diode, variable optical attenuator, and polarization beam combiner.
WDM-compatible integrated photonic computing core for implementing a neural network

We propose and design an energy-efficient integrated photonic computing core by using a microdisk resonator-assisted Mach-Zehnder interferometer. With the use of the fabricated silicon photonic chip, an optical convolutional neural network for image classification is experimentally demonstrated.
Batch Denoising via Blahut-Arimoto

In this work, we propose a method for solving batch denoising using the Blahut-Arimoto algorithm (BA). Theoretical results show that our denoising estimation is highly likely to be close to the best result.
Open quantum channel stabilization for twin-field quantum key distribution

We develop a novel technique to stabilize an open channel without using frequency dissemination for twin-field quantum key distribution. A versatile setup is demonstrated at a distance of 615.6 km, achieving the repeater-like behaviour.
Compressed unordered integer sequences with fast direct access

A compressed representation of integer sequences is the key element of different data compression techniques. The variable-length Reverse Multi-Delimiter codes [1] provide a simple and space-efficient solution to the given problem, combining a good compression ratio with fast decoding. In this research, we investigate another property of RMD-codes - the ability of direct access to codewords in the encoded bitstream. If integers are sorted and the deltas between them are small enough, the problem of direct access is reduced to performing the select operation on a bitmap. However, RMD-codes allow us to address the more general problem of direct access to elements of an unordered integer sequence given in a compressed form. We developed the method of extracting and decoding a codeword from an RMD-bitstream in almost constant time. In text compression, the solution is highly space-saving as the RMD-code size is close to the entropy and extra data structures are tiny.