| Challenge: | Current research on spoken language translation (SLT) has to confront the scarcity of sizeable and publicly available training corpora. |
| Approach: | They propose a multilingual speech translation corpus that will facilitate the training of end-to-end systems for SLT from English into 8 languages. |
| Outcome: | The proposed multilingual speech translation corpus will facilitate the training of end-to-end systems for spoken language translation from English into 8 languages. |
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| Challenge: | Simultaneous speech translation (SiST) begins translating before the entire source input is received. |
| Approach: | They propose a dataset that rearranges sentences into segmented monotonic data for simultaneous speech translation using the Large Language Model. |
| Outcome: | The proposed dataset improves quality and latency in siST translations by rearranging sentences into segmented monotonic data. |
MuST-Cinema: a Speech-to-Subtitles corpus (2020.lrec-1)
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| Challenge: | Existing methods for subtitling are laborious and costly, says aaron sanchez . he says the current methods are laboriously complex and require manual work . |
| Approach: | They propose to use TED subtitles to build a multilingual speech translation corpus . they propose to annotate existing subtitling corpora with subtitle breaks . |
| Outcome: | The proposed model can be used to segment sentences into subtitles and reduces human work . the proposed model reduces the time and cost of human subtitling tasks . |
Rethinking and Improving Multi-task Learning for End-to-end Speech Translation (2023.emnlp-main)
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| Challenge: | auxiliary tasks are highly consistent with end-to-end speech translation (ST) but their effectiveness has not been thoroughly studied. |
| Approach: | They propose an improved multi-task learning approach for the ST task that bridges the modal gap by mitigating the difference in length and representation. |
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CoVoST: A Diverse Multilingual Speech-To-Text Translation Corpus (2020.lrec-1)
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| Challenge: | Existing datasets involve language pairs with English as source language, are low resource or lack labeled data. |
| Approach: | They propose a multilingual speech-to-text translation corpus from 11 languages into English . they provide empirical evidence of the quality of the data and provide initial benchmarks . |
| Outcome: | The proposed model is the first end-to-end multilingual model for spoken language translation. |
MUST&P-SRL: Multi-lingual and Unified Syllabification in Text and Phonetic Domains for Speech Representation Learning (2023.emnlp-industry)
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| Challenge: | Modern speech technologies have moved towards end-to-end models that constitutes black box systems that do not allow for explainability of the prediction or decisions. |
| Approach: | They propose a method for linguistic feature extraction that uses phonetic transcriptions and a forced alignment tool to extract phonetic features. |
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CVSS Corpus and Massively Multilingual Speech-to-Speech Translation (2022.lrec-1)
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| Challenge: | Existing work on speech-to-speech translation (S2ST) systems rely on text representation, but they are text-centric. |
| Approach: | They introduce a massively multilingual-to-English speech-tospeech translation corpus . they synthesize the translation text from the Common Voice speech corpus and CoVoST 2 into English . |
| Outcome: | The proposed corpus outperforms existing models on CoVoST 2 by 5.8 BLEU . the proposed model outperformed the previous state-of-the-art model without extra data . |
Khan Academy Corpus: A Multilingual Corpus of Khan Academy Lectures (2024.lrec-main)
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| Challenge: | a dataset of 10122 hours in 87394 recordings is presented in a new journal . 43% of recordings have human-written subtitles, covering a total of 137 languages. |
| Approach: | They present a Khan Academy corpus with 10122 hours in 87394 recordings . 43% of recordings have human-written subtitles, and 137 languages are included . |
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Augmenting Librispeech with French Translations: A Multimodal Corpus for Direct Speech Translation Evaluation (L18-1)
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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. |
| Approach: | They propose to augment an existing (monolingual) corpus: LibriSpeech. |
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The Multilingual Microblog Translation Corpus: Improving and Evaluating Translation of User-Generated Text (2022.lrec-1)
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| Challenge: | a corpus of over 200,000 microblog translations supports translation of thirteen languages into English . large collections of parallel text, or bitext, are increasingly available in many languages . |
| Approach: | They propose a corpus of over 200,000 microblog posts that supports translation of thirteen languages into English. |
| Outcome: | The proposed corpus contains over 200,000 translations of microblog posts in 13 languages . fine-tuning showed significant improvements in translation quality . |
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. |