19 citations · 29 across the 27 of their papers we have counts for
4 papers · 1 filter
Speaker Verification with Speech-Aware LLMs: Evaluation and Augmentation
Thomas Thebaud, Yuzhe Wang, Laureano Moro-Velazquez +2
Speech-aware large language models (LLMs) can accept speech inputs, yet their training objectives largely emphasize linguistic content or specific fields such as emotions or the sp…
Vox-Profile: A Speech Foundation Model Benchmark for Characterizing Diverse Speaker Traits and Speech Properties
Tiantian Feng, Jihwan Lee, Anfeng Xu +9
We introduce Vox-Profile, a comprehensive benchmark to characterize rich speaker traits and speech properties using speech foundation models. Unlike prior work that targets a singl…
Pathological voice adaptation with autoencoder-based voice conversion
Marc Illa, Bence Mark Halpern, Rob van Son +2
In this paper, we propose a new approach to pathological speech synthesis. Instead of using healthy speech as a source, we customise an existing pathological speech sample to a new…
CopyPaste: An Augmentation Method for Speech Emotion Recognition
Raghavendra Pappagari, Jesús Villalba, Piotr Żelasko +2
Data augmentation is a widely used strategy for training robust machine learning models. It partially alleviates the problem of limited data for tasks like speech emotion recogniti…