We introduce FLEURS, the Few-shot Learning Evaluation of Universal Representations of
Speech benchmark. FLEURS is an n-way parallel speech dataset in 102 languages built on …

Dementia is a progressive neurodegenerative disease that burdens the person living with
the disease, their families, and medical and social services. Timely diagnosis of dementia …

While dynamic Neural Radiance Fields (NeRF) have shown success in high-fidelity 3D
modeling of talking portraits, the slow training and inference speed severely obstruct their …

The goal of voice conversion is to transform source speech into a target voice, keeping the
content unchanged. In this paper, we focus on self-supervised representation learning for …

Recent progress in self-training, self-supervised pretraining and unsupervised learning
enabled well performing speech recognition systems without any labeled data. However, in …

Multilingual Automatic Speech Recognition (ASR) models have extended the usability of
speech technologies to a wide variety of languages. With how many languages these …

Large text corpora are increasingly important for a wide variety of Natural Language
Processing (NLP) tasks, and automatic language identification (LangID) is a core technology …

The primary aim of this study was to contribute to the development of multilingual automatic
speech recognition for lower-resourced Turkic languages. Ten languages—Azerbaijani …

Most recent speech recognition models rely on large supervised datasets, which are
unavailable for many low-resource languages. In this work, we present a speech recognition …

Cross-lingual transfer of knowledge from high-resource languages to low-resource
languages is an important research problem in automatic speech recognition (ASR). We …