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Found 6 papers, 1 papers with code
Infusing Future Information into Monotonic Attention Through Language Models
Simultaneous neural machine translation(SNMT) models start emitting the target sequence before they have processed the source sequence.
TASK AWARE MULTI-TASK LEARNING FOR SPEECH TO TEXT TASKS
In general, the direct Speech-to-text translation (ST) is jointly trained with Automatic Speech Recognition (ASR), and Machine Translation (MT) tasks.
Ranked #1 on
Speech-to-Text Translation
on MuST-C EN->DE
(using extra training data)
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+5
Faster Re-translation Using Non-Autoregressive Model For Simultaneous Neural Machine Translation
The current re-translation approaches are based on autoregressive sequence generation models (ReTA), which generate tar-get tokens in the (partial) translation sequentially.
Data Efficient Direct Speech-to-Text Translation with Modality Agnostic Meta-Learning
In the meta-learning phase, the parameters of the model are exposed to vast amounts of speech transcripts (e. g., English ASR) and text translations (e. g., English-German MT).
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+6
Taxonomy grounded aggregation of classifiers with different label sets
We describe the problem of aggregating the label predictions of diverse classifiers using a class taxonomy.
