371 citations · 453 across the 10 of their papers we have counts for
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A Brief Overview of Unsupervised Neural Speech Representation Learning
Lasse Borgholt, Jakob Drachmann Havtorn, Joakim Edin +2
Unsupervised representation learning for speech processing has matured greatly in the last few years. Work in computer vision and natural language processing has paved the way, but…
Benchmarking Generative Latent Variable Models for Speech
Jakob D. Havtorn, Lasse Borgholt, Søren Hauberg +2
Stochastic latent variable models (LVMs) achieve state-of-the-art performance on natural image generation but are still inferior to deterministic models on speech. In this paper, w…
Do We Still Need Automatic Speech Recognition for Spoken Language Understanding?
Lasse Borgholt, Jakob Drachmann Havtorn, Mostafa Abdou +4
Spoken language understanding (SLU) tasks are usually solved by first transcribing an utterance with automatic speech recognition (ASR) and then feeding the output to a text-based…
Do End-to-End Speech Recognition Models Care About Context?
Lasse Borgholt, Jakob Drachmann Havtorn, Željko Agić +3
The two most common paradigms for end-to-end speech recognition are connectionist temporal classification (CTC) and attention-based encoder-decoder (AED) models. It has been argued…
On Scaling Contrastive Representations for Low-Resource Speech Recognition
Lasse Borgholt, Tycho Max Sylvester Tax, Jakob Drachmann Havtorn +2
Recent advances in self-supervised learning through contrastive training have shown that it is possible to learn a competitive speech recognition system with as little as 10 minute…