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Found 20 papers, 13 papers with code
How do Hyenas deal with Human Speech? Speech Recognition and Translation with ConfHyena
The attention mechanism, a cornerstone of state-of-the-art neural models, faces computational hurdles in processing long sequences due to its quadratic complexity.
Speech Translation with Speech Foundation Models and Large Language Models: What is There and What is Missing?
The field of natural language processing (NLP) has recently witnessed a transformative shift with the emergence of foundation models, particularly Large Language Models (LLMs) that have revolutionized text-based NLP.
Integrating Language Models into Direct Speech Translation: An Inference-Time Solution to Control Gender Inflection
When translating words referring to the speaker, speech translation (ST) systems should not resort to default masculine generics nor rely on potentially misleading vocal traits.
Leveraging Timestamp Information for Serialized Joint Streaming Recognition and Translation
The growing need for instant spoken language transcription and translation is driven by increased global communication and cross-lingual interactions.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+2
Direct Models for Simultaneous Translation and Automatic Subtitling: FBK@IWSLT2023
This paper describes the FBK's participation in the Simultaneous Translation and Automatic Subtitling tracks of the IWSLT 2023 Evaluation Campaign.
Token-Level Serialized Output Training for Joint Streaming ASR and ST Leveraging Textual Alignments
In real-world applications, users often require both translations and transcriptions of speech to enhance their comprehension, particularly in streaming scenarios where incremental generation is necessary.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+1
AlignAtt: Using Attention-based Audio-Translation Alignments as a Guide for Simultaneous Speech Translation
Attention is the core mechanism of today's most used architectures for natural language processing and has been analyzed from many perspectives, including its effectiveness for machine translation-related tasks.
When Good and Reproducible Results are a Giant with Feet of Clay: The Importance of Software Quality in NLP
Despite its crucial role in research experiments, code correctness is often presumed only on the basis of the perceived quality of results.
Attention as a Guide for Simultaneous Speech Translation
The study of the attention mechanism has sparked interest in many fields, such as language modeling and machine translation.
Joint Speech Translation and Named Entity Recognition
Modern automatic translation systems aim at place the human at the center by providing contextual support and knowledge.
Direct Speech Translation for Automatic Subtitling
Automatic subtitling is the task of automatically translating the speech of audiovisual content into short pieces of timed text, i. e. subtitles and their corresponding timestamps.
Dodging the Data Bottleneck: Automatic Subtitling with Automatically Segmented ST Corpora
Speech translation for subtitling (SubST) is the task of automatically translating speech data into well-formed subtitles by inserting subtitle breaks compliant to specific displaying guidelines.
Over-Generation Cannot Be Rewarded: Length-Adaptive Average Lagging for Simultaneous Speech Translation
Simultaneous speech translation (SimulST) systems aim at generating their output with the lowest possible latency, which is normally computed in terms of Average Lagging (AL).
Efficient yet Competitive Speech Translation: FBK@IWSLT2022
The primary goal of this FBK's systems submission to the IWSLT 2022 offline and simultaneous speech translation tasks is to reduce model training costs without sacrificing translation quality.
Does Simultaneous Speech Translation need Simultaneous Models?
In simultaneous speech translation (SimulST), finding the best trade-off between high translation quality and low latency is a challenging task.
Visualization: the missing factor in Simultaneous Speech Translation
Simultaneous speech translation (SimulST) is the task in which output generation has to be performed on partial, incremental speech input.
Speechformer: Reducing Information Loss in Direct Speech Translation
Transformer-based models have gained increasing popularity achieving state-of-the-art performance in many research fields including speech translation.
Ranked #1 on
Speech-to-Text Translation
on MuST-C EN->NL
Simultaneous Speech Translation for Live Subtitling: from Delay to Display
Experiments on three language pairs (en$\rightarrow$it, de, fr) show that scrolling lines is the only mode achieving an acceptable reading speed while keeping delay close to a 4-second threshold.
Mixtures of Deep Neural Experts for Automated Speech Scoring
The paper copes with the task of automatic assessment of second language proficiency from the language learners' spoken responses to test prompts.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+2
Dealing with training and test segmentation mismatch: FBK@IWSLT2021
Both knowledge distillation and the first fine-tuning step are carried out on manually segmented real and synthetic data, the latter being generated with an MT system trained on the available corpora.
