Challenge: a project aims to create an integrated archive of the recordings, scanned documents and photographs from totalitarian regimes in Czechoslovakia . the archive will be accessible online and provide multifaceted search capabilities .
Approach: They propose to use automatic speech recognition and optical character recognition to build an archive of the interviews, scanned documents and photographs.
Outcome: The proposed archive will be accessible online and provide multifaceted search capabilities.

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Improved Transcription and Indexing of Oral History Interviews for Digital Humanities Research (L18-1)

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Challenge: Existing methods to improve transcription and indexing quality of Oral History interviews are not available.
Approach: They propose to use a German Oral History test-set to improve transcription and indexing quality . they propose to combine acoustic modeling techniques with sophisticated neural networks .
Outcome: The proposed system reduces word error rate by 28.3% on German Oral History test-set compared to baseline system . the Fraunhofer IAIS Audio Mining system can process long audio-files to automatically create time-aligned transcriptions.
A Bird’s-eye View of Language Processing Projects at the Romanian Academy (L18-1)

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Challenge: a recent article outlines five projects that address contemporary Romanian language . the authors argue that a constant accumulation of human expertise is needed to develop complex projects.
Approach: a new article gives a general overview of five AI language-related projects at the Romanian Academy . they focus on the creation of a contemporary Romanian language text and speech corpus and language related applications .
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A CLARIN Transcription Portal for Interview Data (2020.lrec-1)

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Challenge: a transcription portal for audio files based on automatic speech recognition (ASR) is implemented in the CLARIN resources research network and intended for use by non-technical scholars.
Approach: They propose a transcription portal for audio files based on automatic speech recognition in various languages.
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A Recorded Debating Dataset (L18-1)

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Challenge: Existing research in computational argumentation and debating technologies focuses on argumentation mining, but other tasks are being addressed as well.
Approach: They describe a dataset of debating speeches in English that is used for research . they use an automatic speech recognition system to produce a more "nLP-friendly" text .
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Using Automatic Speech Recognition in Spoken Corpus Curation (2020.lrec-1)

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Challenge: Automatic Speech Recognition (ASR) is a new way to make audio-visual data accessible.
Approach: They propose to use automatic speech recognition (ASR) to make audio-visual data accessible by systematic queries.
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Text Mining for History: first steps on building a large dataset (L18-1)

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Challenge: a new corpus on the history domain is being created to mine text in the domain . primary motivation for the project is the need to query the material in a non-linear way .
Approach: They propose to use a Brazilian historical-biographical dictionary as a resource for text mining.
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Automatic Orality Identification in Historical Texts (2020.lrec-1)

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Challenge: a set of general linguistic features are used to identify conceptually-oral historical texts . linguists recognize that there is also a lot of variation within discourse modes .
Approach: They propose to use general linguistic features to identify conceptually-oral historical texts . they find they are useful for determining conceptuality of historical data as for modern data .
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An Application for Building a Polish Telephone Speech Corpus (L18-1)

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Challenge: Specifically, we describe a tool designed to improve our Automatic Speech Recognition system performance.
Approach: They propose to build a tool for speech corpus collection of a specific domain content.
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Large Corpus of Czech Parliament Plenary Hearings (2020.lrec-1)

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Challenge: a corpus of Czech parliament plenary sessions is a valuable resource for future research . only a few public datasets are available in the Czech language . end-to-end approaches require extensive training data to produce competitive results .
Approach: They present a corpus of Czech parliament plenary sessions which is a large corpus . they combine a traditional approach with a more traditional approach .
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Creating a Data Set of Abstractive Summaries of Turn-labeled Spoken Human-Computer Conversations (2022.lrec-1)

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Challenge: Digital recorded written and spoken dialogues are becoming more available due to the growing popularity of online messenger services and chatbots.
Approach: They propose to use Dutch spoken human-computer conversations, an annotation layer of turn labels, and conversational abstractive summaries of user answers to build a conversational agent.
Outcome: The proposed system can be integrated into a conversational agent.

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