CoVoST-2
Emerging32papers using it
2022first seen
CoVoST-2 is a multilingual speech-to-text translation benchmark that contains a diverse set of speech data across multiple languages, used to evaluate the performance of machine translation systems.
Papers using CoVoST-2 (29)
- Llast: Improved End-to-end Speech Translation System Leveraged By Large Language ModelsSample, Translate, Recombine: Leveraging Audio Alignments For Data Augmentation In End-to-end Speech TranslationCTC-GMM: CTC Guided Modality Matching For Fast And Accurate Streaming Speech TranslationPrepending or Cross-Attention for Speech-to-Text? An Empirical
ComparisonScalable Multilingual Multimodal Machine Translation with Speech-Text FusionPART: Progressive Alignment Representation Training for Multilingual Speech-To-Text with LLMsSASST: Leveraging Syntax-Aware Chunking and LLMs for Simultaneous Speech TranslationSpeech Translation Refinement using Large Language ModelsImproving End-to-end Speech Translation By Imitation-based Knowledge Distillation With Synthetic TranscriptsInvestigating Decoder-only Large Language Models For Speech-to-text TranslationImproving Cascaded Unsupervised Speech Translation With Denoising Back-translationComsl: A Composite Speech-language Model For End-to-end Speech-to-text TranslationPre-training for Speech Translation: CTC Meets Optimal TransportSimple and Effective Unsupervised Speech TranslationImproving Cascaded Unsupervised Speech Translation with Denoising
Back-translationComSL: A Composite Speech-Language Model for End-to-End Speech-to-Text
TranslationMake More of Your Data: Minimal Effort Data Augmentation for Automatic
Speech Recognition and TranslationLLaST: Improved End-to-end Speech Translation System Leveraged by Large
Language ModelsImproved Cross-Lingual Transfer Learning For Automatic Speech
TranslationImproving End-to-End Speech Translation by Imitation-Based Knowledge
Distillation with Synthetic TranscriptsTowards a Deep Understanding of Multilingual End-to-End Speech
TranslationGenTranslate: Large Language Models are Generative Multilingual Speech
and Machine TranslatorsCompact Speech Translation Models via Discrete Speech Units PretrainingInvestigating Decoder-only Large Language Models for Speech-to-text
TranslationTask Arithmetic for Language Expansion in Speech TranslationMaking LLMs Better Many-to-Many Speech-to-Text Translators with Curriculum LearningCTC-GMM: CTC guided modality matching for fast and accurate streaming
speech translationRepresentation Purification for End-to-End Speech TranslationZero-resource Speech Translation and Recognition with LLMs