Unsupervised speech representations have taken off, with benchmarks (SUP...
Recent progress in self-supervised or unsupervised machine learning has
...
Word or word-fragment based Language Models (LM) are typically preferred...
Several deep neural networks have recently been shown to generate activa...
Our native language influences the way we perceive speech sounds, affect...
Self-supervised models for speech processing form representational space...
We present the Zero Resource Speech Challenge 2021, which asks participa...
Many types of distributional word embeddings (weakly) encode linguistic
...
We introduce a new unsupervised task, spoken language modeling: the lear...
We present the Zero Resource Speech Challenge 2020, which aims at learni...
In this paper, we present a data set and methods to compare speech proce...
Vector space models of words have long been claimed to capture linguisti...
We present the Perceptimatic English Benchmark, an open experimental
ben...
Reconstruction of articulatory trajectories from the acoustic speech sig...
We present the Zero Resource Speech Challenge 2019, which proposes to bu...
Recurrent neural networks (RNNs) can learn continuous vector representat...
We describe a new challenge aimed at discovering subword and word units ...
Recent works have explored deep architectures for learning multimodal sp...