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Found 6 papers, 4 papers with code
End-to-End Evaluation for Low-Latency Simultaneous Speech Translation
Secondly, we compare different approaches to low-latency speech translation using this framework.
KIT's Multilingual Speech Translation System for IWSLT 2023
In this paper, we describe our speech translation system for the multilingual track of IWSLT 2023, which evaluates translation quality on scientific conference talks.
Perturbation-based QE: An Explainable, Unsupervised Word-level Quality Estimation Method for Blackbox Machine Translation
Quality Estimation (QE) is the task of predicting the quality of Machine Translation (MT) system output, without using any gold-standard translation references.
E2EG: End-to-End Node Classification Using Graph Topology and Text-based Node Attributes
Node classification utilizing text-based node attributes has many real-world applications, ranging from prediction of paper topics in academic citation graphs to classification of user characteristics in social media networks.
Ranked #38 on
Node Property Prediction
on ogbn-products
Tackling data scarcity in speech translation using zero-shot multilingual machine translation techniques
We investigate whether these ideas can be applied to speech translation, by building ST models trained on speech transcription and text translation data.
Zero-shot Speech Translation
The challenge is that the representation of text and audio is significantly different, thus the models learn ASR and MT tasks in different ways, making it non-trivial to perform zero-shot.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+3
