4 papers · 1 filter
An Evaluation Framework for Text-to-Speech Voice Reconstruction
Ariadna Sanchez, Christoph Minixhofer, Korin Richmond +3
Voice reconstruction using Text-to-Speech (TTS) offers a communication method for people with speech disorders, which aims to retain their speaker identity while improving intellig…
LISE : Listenable Interpretable Speaker Embeddings
Xiaoliang Wu, Chongxin Gan, Ke Liu +2
Deep neural network-based automatic speaker verification (ASV) systems achieve impressive performance but their embedding representations remain opaque, lacking a structured and pe…
From Seeing it to Experiencing it: Interactive Evaluation of Intersectional Voice Bias in Human-AI Speech Interaction
Shree Harsha Bokkahalli Satish, Maria Teleki, Christoph Minixhofer +3
SpeechLLMs process spoken language directly from audio, but accent and vocal identity cues can lead to biased behaviour. Current bias evaluations often miss how such bias manifests…
The Voice Behind the Words: Quantifying Intersectional Bias in SpeechLLMs
Shree Harsha Bokkahalli Satish, Christoph Minixhofer, Maria Teleki +5
Speech Large Language Models (SpeechLLMs) process spoken input directly, retaining cues such as accent and perceived gender that were previously removed in cascaded pipelines. This…