Challenge: Praaline is an open-source software system for constituting and managing spoken language and multimodal corpora.
Approach: They present the latest developments of Praaline, an open-source software system for constituting and managing spoken language and multimodal corpora.
Outcome: The proposed system can be used for creating, managing, visualising and analysing spoken language and multimodal corpora.

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The DReaM Corpus: A Multilingual Annotated Corpus of Grammars for the World’s Languages (2020.lrec-1)

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Challenge: Until recently, language descriptions were available in paper form only, with indexes as the only search aid.
Approach: They propose to digitize a multilingual corpus of language descriptions and annotate it with various meta, word, and text attributes to make searching and analysis easier and more useful.
Outcome: The proposed corpus is searchable through a couple of well-established corpus infrastructures.
Open-source Multi-speaker Speech Corpora for Building Gujarati, Kannada, Malayalam, Marathi, Tamil and Telugu Speech Synthesis Systems (2020.lrec-1)

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Challenge: We present free high quality multi-speaker speech corpora for Gujarati, Kannada, Malayalam, Marathi, Tamil and Telugu . the datasets are primarily intended for use in text-to-speech applications, such as constructing multilingual voices or language adaptation.
Approach: They present a free high quality multi-speaker speech corpora for Gujarati, Kannada, Malayalam, Marathi, Tamil and Telugu . they use it to build a multilingual text-to-speech model that can be scaled to other languages of interest.
Outcome: The proposed model produces good quality voices with MOS > 3.6 for all the languages tested.
An Empirical Evaluation of Annotation Practices in Corpora from Language Documentation (2020.lrec-1)

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Challenge: Language documentation projects have produced substantial amounts of primary data from a wide variety of endangered languages.
Approach: They propose to use common annotation conventions in existing corpora to facilitate their future processing.
Outcome: The proposed formats are based on the common ELAN and Toolbox formats and are used to facilitate their future processing.
Compilation of Corpora for the Study of the Information Structure–Prosody Interface (L18-1)

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Challenge: empirical studies on the Information Structure-prosody interface are scarce . thematicity defines how content is packaged in terms of "what is being talked about" a different view on thematicality is advocated by I. Mel'uk in the context of the MTT.
Approach: They propose a method for the compilation of annotated corpora to study the correspondence between Information Structure and prosody.
Outcome: The proposed method is applied to a corpus of read speech in English annotated with hierarchical thematicity and automatically extracted prosodic parameters.
CEASR: A Corpus for Evaluating Automatic Speech Recognition (2020.lrec-1)

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Challenge: Automatic Speech Recognition (ASR) systems are increasingly needed for research and practical applications.
Approach: They propose to use public speech corpora to evaluate the quality of automatic speech recognition (ASR) they calculate an average Word Error Rate (WER) per corpus, per system and per corpor-system pair .
Outcome: The proposed corpus evaluates the quality of automatic speech recognition systems using public speech corpora and transcripts generated by state-of-the-art systems.
Praat++: Multimedia Annotation System for Speech and Vocalization (2026.acl-demo)

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Challenge: High-quality time-aligned annotation is fundamental to speech processing and animal vocalization research, yet precise boundary localization and consistent labeling remain challenging in collaborative settings.
Approach: They propose a web-based multimedia annotation system for collaborative, video-informed, and AI-assisted timeline labeling of audio and video data.
Outcome: The proposed system improves time-aligned labeling and accuracy in speech and animal vocalization annotations.
A Short Survey on Sense-Annotated Corpora (2020.lrec-1)

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Challenge: Word Sense Disambiguation (WSD) is a key task in Natural Language Understanding.
Approach: They propose to use sense-annotated corpora for supervised Word Sense Disambiguation.
Outcome: The proposed methods have been compared with knowledge-based approaches and have shown to be more efficient when they are available.
A Repository of Corpora for Summarization (L18-1)

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Challenge: Summarization corpora are numerous but fragmented, making it difficult to pinpoint corporata best suited for a given summarization task.
Approach: They propose a repository containing corpora available to train and evaluate automatic summarization systems.
Outcome: The proposed system is based on a repository of corpora available for summarization tasks.
A Modular Tool for Automatic Summarization (P19-3)

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Challenge: Abstractive automatic summarization methods are supervized, but they require large corpora to perform tasks.
Approach: They propose to use a modular tool for automatic summarization that is as simple as possible for end-users.
Outcome: The proposed tool is open source and written in Java . it could be used as a baseline for future work and evaluate methods on different corpora.
A Brief Survey of Textual Dialogue Corpora (2022.lrec-1)

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Challenge: Several dialogue corpora are available for research purposes, but they do not cover all the necessities of real-world applications.
Approach: They analyze available dialogue corpora and propose possible approaches to create new ones.
Outcome: The proposed corpus of human-human dialogues is based on a list of available dialogue corpora . it covers speakers, size, languages, collection, annotations, and domains . some trends are identified and possible approaches are also discussed .

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