MUSTC
Emerging48papers using it
2021first seen
The MUSTC dataset is a benchmark used to evaluate speech translation tasks, containing multi-view speech representations for assessing model performance.
Papers using MUSTC (48)
- SimulU: Training-free Policy for Long-form Simultaneous Speech-to-Speech TranslationOptimal Multi-Task Learning at Regularization Horizon for Speech Translation TaskInfiniSST: Simultaneous Translation of Unbounded Speech with Large Language ModelOptimizing Speech Multi-View Feature Fusion through Conditional
ComputationSpeech Translation Refinement using Large Language ModelsM3ST: Mix at Three Levels for Speech TranslationPre-training for Speech Translation: CTC Meets Optimal TransportEfficient Sequence Transduction by Jointly Predicting Tokens and
DurationsSHAS: Approaching optimal Segmentation for End-to-End Speech TranslationSpeechUT: Bridging Speech and Text with Hidden-Unit for Encoder-Decoder
Based Speech-Text Pre-trainingRegularizing End-to-End Speech Translation with Triangular Decomposition
AgreementSTEMM: Self-learning with Speech-text Manifold Mixup for Speech
TranslationGigaST: A 10,000-hour Pseudo Speech Translation CorpusSimple and Effective Unsupervised Speech TranslationAdaTranS: Adapting with Boundary-based Shrinking for End-to-End Speech
TranslationWACO: Word-Aligned Contrastive Learning for Speech TranslationTuning Large language model for End-to-end Speech TranslationT-Modules: Translation Modules for Zero-Shot Cross-Modal Machine
TranslationEfficient Speech Translation with Dynamic Latent PerceiversSegAugment: Maximizing the Utility of Speech Translation Data with
Segmentation-based AugmentationsHybrid Transducer and Attention based Encoder-Decoder Modeling for
Speech-to-Text TasksUnderstanding and Bridging the Modality Gap for Speech TranslationCMOT: Cross-modal Mixup via Optimal Transport for Speech TranslationSoft Alignment of Modality Space for End-to-end Speech TranslationFASST: Fast LLM-based Simultaneous Speech TranslationUnified Speech-Text Pre-training for Speech Translation and RecognitionCross-modal Contrastive Learning for Speech TranslationGenerating Synthetic Speech from SpokenVocab for Speech TranslationRedApt: An Adaptor for wav2vec 2 Encoding \\ Faster and Smaller Speech
Translation without Quality CompromiseDecouple Non-parametric Knowledge Distillation For End-to-end Speech
TranslationImproving speech translation by fusing speech and textCTC-based Non-autoregressive Speech TranslationSpeech Translation with Foundation Models and Optimal Transport: UPC at
IWSLT23Modality Adaption or Regularization? A Case Study on End-to-End Speech
TranslationShiftable Context: Addressing Training-Inference Context Mismatch in
Simultaneous Speech TranslationImplicit Memory Transformer for Computationally Efficient Simultaneous
Speech TranslationImproving End-to-End Speech Translation by Imitation-Based Knowledge
Distillation with Synthetic TranscriptsAn Empirical Study of Consistency Regularization for End-to-End
Speech-to-Text TranslationBridging the Gaps of Both Modality and Language: Synchronous Bilingual
CTC for Speech Translation and Speech RecognitionCross-Modal Multi-Tasking for Speech-to-Text Translation via Hard
Parameter SharingRethinking and Improving Multi-task Learning for End-to-end Speech
TranslationPushing the Limits of Zero-shot End-to-End Speech TranslationSimulTron: On-Device Simultaneous Speech to Speech TranslationTask Arithmetic for Language Expansion in Speech TranslationRepresentation Purification for End-to-End Speech TranslationOn the Impact of Noises in Crowd-Sourced Data for Speech TranslationImproving Speech Translation by Cross-Modal Multi-Grained Contrastive
LearningIncremental Blockwise Beam Search for Simultaneous Speech Translation
with Controllable Quality-Latency Tradeoff