4 papers
Which Data Matter? Embedding-Based Data Selection for Speech Recognition
Zakaria Aldeneh, Skyler Seto, Maureen de Seyssel +8
Modern ASR systems are typically trained on large-scale pseudo-labeled, in-the-wild data spanning multiple domains. While such heterogeneous data benefit generalist models designed…
Discriminating Form and Meaning in Multilingual Models with Minimal-Pair ABX Tasks
Maureen de Seyssel, Jie Chi, Skyler Seto +3
We introduce a set of training-free ABX-style discrimination tasks to evaluate how multilingual language models represent language identity (form) and semantic content (meaning). I…
Leveraging Audio-Visual Data to Reduce the Multilingual Gap in Self-Supervised Speech Models
MarÃa Andrea Cruz Blandón, Zakaria Aldeneh, Jie Chi +1
Self-supervised learning (SSL) has made significant advances in speech representation learning. Models like wav2vec 2.0 and HuBERT have achieved state-of-the-art results in tasks s…
The Role of Prosody in Spoken Question Answering
Jie Chi, Maureen de Seyssel, Natalie Schluter
Spoken language understanding research to date has generally carried a heavy text perspective. Most datasets are derived from text, which is then subsequently synthesized into spee…