1 citations · 1 across the 9 of their papers we have counts for
10 papers
A Cross Community Agenda for Speech AI
Maria Teleki, Kimi Wenzel, Anna Seo Gyeong Choi +20
Speech AI, any AI system that recognizes, transforms, or generates speech, is built and evaluated across two communities with only a small overlap: technical natural language proce…
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…
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…
Prosodic Structure Beyond Lexical Content: A Study of Self-Supervised Learning
Sarenne Wallbridge, Christoph Minixhofer, Catherine Lai +1
People exploit the predictability of lexical structures during text comprehension. Though predictable structure is also present in speech, the degree to which prosody, e.g. intonat…
TTSDS2: Resources and Benchmark for Evaluating Human-Quality Text to Speech Systems
Christoph Minixhofer, Ondrej Klejch, Peter Bell
Evaluation of Text to Speech (TTS) systems is challenging and resource-intensive. Subjective metrics such as Mean Opinion Score (MOS) are not easily comparable between works. Objec…
Beyond Oversmoothing: Evaluating DDPM and MSE for Scalable Speech Synthesis in ASR
Christoph Minixhofer, Ondrej Klejch, Peter Bell
Synthetically generated speech has rapidly approached human levels of naturalness. However, the paradox remains that ASR systems, when trained on TTS output that is judged as natur…
TTSDS -- Text-to-Speech Distribution Score
Christoph Minixhofer, Ondřej Klejch, Peter Bell
Many recently published Text-to-Speech (TTS) systems produce audio close to real speech. However, TTS evaluation needs to be revisited to make sense of the results obtained with th…
Evaluating and reducing the distance between synthetic and real speech distributions
Christoph Minixhofer, Ondřej Klejch, Peter Bell
While modern Text-to-Speech (TTS) systems can produce natural-sounding speech, they remain unable to reproduce the full diversity found in natural speech data. We consider the dist…
Mask-combine Decoding and Classification Approach for Punctuation Prediction with real-time Inference Constraints
Christoph Minixhofer, Ondřej Klejch, Peter Bell
In this work, we unify several existing decoding strategies for punctuation prediction in one framework and introduce a novel strategy which utilises multiple predictions at each w…