March 2, 2020 Presentation Open Access

Henk van den Heuvel; Christoph Draxler

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    <subfield code="a">&lt;p&gt;&lt;strong&gt;A high-quality orthographic transcript is the basis for all types of analyses of spoken language data. However, transcribing speech is a time-consuming and tedious task. But automatic speech recognition as well as NLP and text annotation tools can make this task much quicker and save you a lot of time and frustration.&lt;/strong&gt;&lt;/p&gt;

&lt;p&gt;In this first of a series of&amp;nbsp;&lt;a href="https://www.sshopencloud.eu/"&gt;SSHOC&lt;/a&gt;&amp;nbsp;webinars,&amp;nbsp;organised by the consortium partner&amp;nbsp;&lt;a href="https://www.clarin.eu/"&gt;&lt;strong&gt;CLARIN ERIC,&lt;/strong&gt;&lt;/a&gt;&amp;nbsp;we will discuss the theoretical basis and the technology available for transcribing spoken language. In particular, we will focus on the role of automatic speech recognition &amp;ndash; what are the opportunities, what are the pitfalls and to where can it be applied successfully.&lt;/p&gt;

&lt;p&gt;&lt;strong&gt;ABOUT THE WEBINAR&lt;/strong&gt;&lt;/p&gt;

&lt;p&gt;&lt;em&gt;&lt;strong&gt;Introduction to working with interview data.&lt;/strong&gt;&lt;/em&gt;&amp;nbsp;Henk van den Heuvel&amp;nbsp;- Head of the Humanities Lab at the Faculty of Arts, Radbound University Nijmegen - will briefly introduce the topic of using interviews as research instrument, and the cross-disciplinary nature of using interview data. He will also give some background on the Transcription Chain initiative which originated from oral history research but has a much larger potential.&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&lt;/p&gt;

&lt;p&gt;&lt;em&gt;&lt;strong&gt;Demonstration of automatic transcription of speech.&lt;/strong&gt;&lt;/em&gt;&amp;nbsp;Christoph Draxler - Researcher at the Institute of Phonetics and Speech Processing at Ludwig Maximilian University Munich - will demonstrate the web portal for the automatic transcription of speech. This portal currently supports three languages (English, German, Dutch), with Italian and Czech in the pipeline. The portal provides a user-friendly interface, so that researchers without a technical background may use state-of-the-art recognizers, optimized annotation editors and powerful segmentation services to result in high-quality time-aligned transcripts. These transcripts are the basis for the following in-depth scientific analysis, e. g. topic modeling, linguistic structures, named entity recognition.&lt;/p&gt;</subfield>
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