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Found 10 papers, 7 papers with code
UFAL Submissions to the IWSLT 2016 MT Track
We present our submissions to the IWSLT 2016 machine translation task, as our first attempt to translate subtitles and one of our early experiments with neural machine translation (NMT).
Jam-ALT: A Formatting-Aware Lyrics Transcription Benchmark
Current automatic lyrics transcription (ALT) benchmarks focus exclusively on word content and ignore the finer nuances of written lyrics including formatting and punctuation, which leads to a potential misalignment with the creative products of musicians and songwriters as well as listeners' experiences.
Ranked #1 on
Automatic Lyrics Transcription
on Jam-ALT Spanish
MoveFormer: a Transformer-based model for step-selection animal movement modelling
In this work, we propose MoveFormer, a new step-based model of movement capable of learning directly from full animal trajectories.
Black-box language model explanation by context length probing
The increasingly widespread adoption of large language models has highlighted the need for improving their explainability.
Relative Positional Encoding for Transformers with Linear Complexity
Recent advances in Transformer models allow for unprecedented sequence lengths, due to linear space and time complexity.
Self-Supervised VQ-VAE for One-Shot Music Style Transfer
While several style conversion methods tailored to musical signals have been proposed, most lack the 'one-shot' capability of classical image style transfer algorithms.
Groove2Groove: One-Shot Music Style Transfer with Supervision from Synthetic Data
Style transfer is the process of changing the style of an image, video, audio clip or musical piece so as to match the style of a given example.
Supervised Symbolic Music Style Translation Using Synthetic Data
Research on style transfer and domain translation has clearly demonstrated the ability of deep learning-based algorithms to manipulate images in terms of artistic style.
Are BLEU and Meaning Representation in Opposition?
One of possible ways of obtaining continuous-space sentence representations is by training neural machine translation (NMT) systems.
Eval all, trust a few, do wrong to none: Comparing sentence generation models
In this paper, we study recent neural generative models for text generation related to variational autoencoders.
