Challenge: A popular idea in Computer Assisted Language Learning (CALL) is to use multimodal annotated texts to support reading.
Approach: They propose to use an open source platform to create good quality audio for L2 learning . they use four passages from LARA versions of Saint-Exupèry’s “Le petit prince” to instantiate the 2x2 cross product of dialogue, not-dialogue and humour, not humor.
Outcome: The proposed method is based on a web form and ten languages.

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Challenge: Recent advances in text-to-speech systems have been driven by large, multi-domain speech corpora.
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Challenge: Recent research has focused on literary machine translation (MT) but evaluation of literary MT remains an open problem.
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Challenge: Text-to-speech (TTS) systems are limited by limited data and linguistic complexities.
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Bahasa Harmony: A Comprehensive Dataset for Bahasa Text-to-Speech Synthesis with Discrete Codec Modeling of EnGen-TTS. (2024.findings-emnlp)

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Challenge: Existing text-to-speech (TTS) systems often fail to address the needs of Bahasa, resulting in limited adaptability, linguistic richness, or efficiency.
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SpeechWeave: Diverse Multilingual Synthetic Text & Audio Data Generation Pipeline for Training Text to Speech Models (2025.acl-industry)

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Challenge: Text-to-Speech (TTS) training requires extensive and diverse text and speech data.
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Prosody-TTS: Improving Prosody with Masked Autoencoder and Conditional Diffusion Model For Expressive Text-to-Speech (2023.findings-acl)

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Challenge: Expressive text-to-speech aims to generate high-quality samples with rich prosody . prosodic attributes in highly dynamic voices are difficult to capture and model without intonation .
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An Automated End-to-End Open-Source Software for High-Quality Text-to-Speech Dataset Generation (2024.lrec-main)

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Challenge: Text-to-speech (TTS) models require data availability and quality of training data.
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Challenge: Existing multilingual TTS datasets are limited in speech generation fields due to lack of quality data.
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Real or Robotic? Assessing Whether LLMs Accurately Simulate Qualities of Human Responses in Human-LLM Dialogue (2026.findings-acl)

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Challenge: Recent work has sought to use large language models to simulate human-human and human-LLM interactions.
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