4 papers
From Speech to Editable Concepts: Probing Emotion Recognition with Concept Bottleneck Models
Hezhao Zhang, Thomas Hain
Speech emotion recognition (SER) is the task of assigning emotion labels to utterances. Early systems relied on acoustic features, whereas recent approaches combine multiple modali…
CS-YODAS: A Mined Dataset of In-the-Wild Code-Switched Speech
Brian Yan, Qingzheng Wang, Matthew Wiesner +9
We present CS-YODAS, a Creative Commons-licensed dataset of in-the-wild code-switched speech mined from multilingual YouTube data. Code-switching (CS), or the alternation between l…
VoxEmo: Benchmarking Speech Emotion Recognition with Speech LLMs
Hezhao Zhang, Huang-Cheng Chou, Shrikanth Narayanan +1
Speech Large Language Models (LLMs) show great promise for speech emotion recognition (SER) via generative interfaces. However, shifting from closed-set classification to open text…
Improving Accented Speech Recognition using Data Augmentation based on Unsupervised Text-to-Speech Synthesis
Cong-Thanh Do, Shuhei Imai, Rama Doddipatla +1
This paper investigates the use of unsupervised text-to-speech synthesis (TTS) as a data augmentation method to improve accented speech recognition. TTS systems are trained with a…