Challenge: a French audiobooks corpus contains 87 hours of good audio quality speech . audiobooks provide mono-genre and multi-speaker speech whereas audiobooks usually provide a few hours of mono- and multispeakers .
Approach: They present an expressive French audiobooks corpus containing eighty seven hours of speech . the corpus is annotated automatically and provides information as phone labels, phone boundaries, syllables, words or morpho-syntactic tagging.
Outcome: The proposed corpus contains 87 hours of speech recorded by a single speaker . the data will allow developing models to better control expressiveness in speech synthesis .

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Challenge: Recent work in spoken language translation (SLT) has attempted to build end-to-end speech-totext translation without using source language transcription during learning or decoding.
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Challenge: Cued Speech is a visual communication system developed for deaf people to complement speechreading at the phonetic level with hands.
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Construction of English-French Multimodal Affective Conversational Corpus from TV Dramas (L18-1)

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Challenge: Existing technologies for speech recognition and speech synthesis focus on non-verbal content and paralinguistic information.
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Challenge: We show that ascribing verbal descriptions to expressive audiovisual utterances is efficient and efficient.
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A (Psycho-)Linguistically Motivated Scheme for Annotating and Exploring Emotions in a Genre-Diverse Corpus (2022.lrec-1)

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Challenge: Using a linguistic perspective, emotion annotation is considered a difficult task because of the lack of consensus on emotional categories, the fuzziness of boundaries between them or the great variability of emotion expressions types.
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A Real-life, French-accented Corpus of Air Traffic Control Communications (L18-1)

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Challenge: AIRBUS-ATC corpus is a real-life, french-accented speech corpus of air traffic control (ATC) communications . it is composed of 59 hours of transcribed English audio, along with linguistic and meta-data annotations.
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LibriVoxDeEn: A Corpus for German-to-English Speech Translation and German Speech Recognition (2020.lrec-1)

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Audiobook Dialogues as Training Data for Conversational Style Synthetic Voices (2022.lrec-1)

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Challenge: Synthetic voices are increasingly used in applications that require a conversational speaking style.
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