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Found 12 papers, 5 papers with code
Large Concept Models: Language Modeling in a Sentence Representation Space
In this paper, we present an attempt at an architecture which operates on an explicit higher-level semantic representation, which we name a concept.
2M-BELEBELE: Highly Multilingual Speech and American Sign Language Comprehension Dataset
We introduce the first highly multilingual speech and American Sign Language (ASL) comprehension dataset by extending BELEBELE.
Unveiling the Role of Pretraining in Direct Speech Translation
Hence, we hypothesize that this issue stems from the difficulty of effectively training an encoder for direct speech translation.
Linguini: A benchmark for language-agnostic linguistic reasoning
We propose a new benchmark to measure a language model's linguistic reasoning skills without relying on pre-existing language-specific knowledge.
Towards Real-World Streaming Speech Translation for Code-Switched Speech
Code-switching (CS), i. e. mixing different languages in a single sentence, is a common phenomenon in communication and can be challenging in many Natural Language Processing (NLP) settings.
SpeechAlign: a Framework for Speech Translation Alignment Evaluation
In doing so, we contribute to the ongoing research progress within the fields of Speech-to-Speech and Speech-to-Text translation.
The Gender-GAP Pipeline: A Gender-Aware Polyglot Pipeline for Gender Characterisation in 55 Languages
We showcase it to report gender representation in WMT training data and development data for the News task, confirming that current data is skewed towards masculine representation.
Multi-View Frequency-Attention Alternative to CNN Frontends for Automatic Speech Recognition
Convolutional frontends are a typical choice for Transformer-based automatic speech recognition to preprocess the spectrogram, reduce its sequence length, and combine local information in time and frequency similarly.
Towards Opening the Black Box of Neural Machine Translation: Source and Target Interpretations of the Transformer
In Neural Machine Translation (NMT), each token prediction is conditioned on the source sentence and the target prefix (what has been previously translated at a decoding step).
Multiformer: A Head-Configurable Transformer-Based Model for Direct Speech Translation
Different approaches have been proposed to overcome these problems, such as the use of efficient attention mechanisms.
On the Locality of Attention in Direct Speech Translation
Transformers have achieved state-of-the-art results across multiple NLP tasks.
Efficient Transformer for Direct Speech Translation
When working with speech, we must face a problem: the sequence length of an audio input is not suitable for the Transformer.
