Fireflies currently supports over 32 languages, so you can transcribe your meetings in any one of the languages you prefer. Right now, Fireflies does not support multiple languages in the same meeting. In contrast, Zoom transcription only supports English.

Unlike phonetic transcription, orthographic translation follows standardised language rule and is unaffected by changes in pronunciation. For example, the popular Australian TV soap Neighbours is known for introducing the upward phonetic inflexion at the end of sentences to the rest of the English-speaking world. While this would be immediately apparent in a phonetic transcription, an orthographic transcription would not indicate any difference. Orthographic transcriptions are the preferred choice for large-scale corpora, particularly that used for research, where details of pronunciation are immaterial

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A simple search-engine enquiry will reveal an assortment of free-to-use transcription tools available for use online. The quality of these free programs can vary tremendously, however, so you should always proofread the captions as it may be peppered with errors. If a video can be uploaded to YouTube, users can take advantage of automatic YouTube captioning, which offers transcriptions with up to 80% accuracy, depending on the sound quality of the video (though, not all languages are supported by YouTube).

Braina seamlessly combines transcription services with virtual assistant features within a single, intuitive interface. Braina users can search online, take notes and select music to play all while transcribing text in over 100 different languages with up to 99% accuracy.

Users can upload documents in any language to Taguette. The interface is currently available in English (US), French, German, Italian, and Spanish. You can find more information about using Taguette via the getting started guide and FAQ.

ROOT is a software framework for data analysis and I/O: a powerful tool to cope with the demanding tasks typical of state of the art scientific data analysis. Among its prominent features are an advanced graphical user interface, ideal for interactive analysis, an interpreter for the C++ programming language, for rapid and efficient prototyping and a persistency mechanism for C++ objects, used also to write every year petabytes of data recorded by the Large Hadron Collider experiments. This introductory guide illustrates the main features of ROOT which are relevant for the typical problems of data analysis: input and plotting of data from measurements and fitting of analytical functions.

ROOT is very flexible and provides both a programming interface to use in own applications and a graphical user interface for interactive data analysis. The purpose of this document is to serve as a beginners guide and provides extendable examples for your own use cases, based on typical problems addressed in student labs. This guide will hopefully lay the ground for more complex applications in your future scientific work building on a modern, state-of the art tool for data analysis.

There are some powerful features of ROOT which were not treated in this document, e.g. packages named RooFit and RooStats providing an advanced framework for model building, fitting and statistical analysis. The ROOT namespace TMVA offers multi-variate analysis tools including an artificial neural network and many other advanced tools for classification problems. The remarkable ability of ROOT to handle large data volumes was already mentioned in this guide, implemented through the class TTree. But there is still much more for you to explore!

Thirdly, while qualitative data analysis can take a wide variety of forms, it largely differs from quantitative research in the focus on language, signs, experiences, and meaning. In addition, qualitative approaches to analysis are often holistic and contextual rather than analyzing the data in a piecemeal fashion or removing the data from its context. Qualitative approaches thus allow researchers to explore inquiries from directions that could not be accessed with only numerical quantitative data.

Deductive analysis is guided by pre-existing theories or ideas. It starts with a theoretical framework, which is then used to code the data. The researcher can thus use this theoretical framework to interpret their data and answer their research question.

The key steps include coding the data based on the predetermined concepts or categories and using the theory to guide the interpretation of patterns among the codings. Deductive analysis is particularly useful when researchers aim to verify or extend an existing theory within a new context.

Discourse analysis is a qualitative research approach that emphasizes the role of language in social contexts. It involves examining communication and language use beyond the level of the sentence, considering larger units of language such as texts or conversations.

What about survey data? Some survey data programs will immediately provide basic descriptive-level analysis of the responses. ATLAS.ti will support you with the analysis of the open-ended questions. For this, you need to export your data as an Excel file. ATLAS.ti's survey import wizard will guide you through the process.

When you enable code scanning, both default and advanced setup generate a CodeQL database for analysis using the simplest method available. For Java, the CodeQL database is generated directly from the codebase without requiring a build (none build mode). For other compiled languages, CodeQL builds the codebase using the autobuild build mode. Alternatively, you can use the manual build mode to specify explicit build commands to analyze only the files that are built by these custom commands.

Note: If your workflow uses a language matrix, autobuild attempts to build each of the compiled languages listed in the matrix. Without a matrix autobuild attempts to build the supported compiled language that has the most source files in the repository. With the exception of Go, analysis of other compiled languages in your repository will fail unless you supply explicit build commands.

If you later add Kotlin code to a repository that uses the none build mode, CodeQL analysis reports a warning message explaining that Kotlin is not supported. You will need to disable default setup and re-enable it. When you re-enable default setup, the build mode will change to autobuild so that both languages can be analyzed. Alternatively, you can change to an advanced setup. For more information, see "Warning: Detected X Kotlin files in your project that could not be processed without a build."

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Statisticians creating epidemiological analyses in R may need to make an analysis available to users who are unfamiliar with the language. A solution is to provide a user-friendly web application for the R script. Values for variables and data files for processing are submitted by the user on a web form. The web application then runs the R script on a server, out of sight of the user, and returns the results of the analysis to the user's web page.

After the import of the data from the BEFdata platform, we can start working with it right away. Furthermore, we are able to inspect the metadata as it is attached as attributes to the R data frame. In our example, we first inspect the metadata of the datasets. This can help in understanding data and guide decisions on merging data into synthesis data products. The R script covering the steps of inspecting the metadata is available via Gists ( ). The scripts covering the analysis parts and the visualization can be found here and here (Hothorn et al. 2008, Weisberg 2011, Pinheiro et al. 2014). Furthermore, the script containing all code of our examples in one file is available via figshare and Gist from here

To prevent SonarScanner CLI from re-downloading language analyzers each time you run a scan, you can mount a directory where the scanner stores the downloads so that the downloads are reused between scanner runs. On some CI systems, you also need to add this directory to your CI cache configuration.

Request official transcripts from all colleges and universities you have attended. If you have fewer than 60 semester (90 quarter) units, transcripts from your secondary school are required as well. Transcripts should be submitted in both your native language and in English. Transcripts will be accepted if mailed directly by the institution or if hand-carried in their original sealed envelope to Cal State East Bay's International Admission Office in the Student Services Hub on the Hayward Campus. 589ccfa754

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