activity
20162026
most citedListen, Denoise, Action! Audio-Driven Motion Synthesis with Diffusion Models

189 citations · 1.4k across the 55 of their papers we have counts for

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Showing 2024Show all

8 papers · 1 filter

cs.CL2024

CARL-GT: Evaluating Causal Reasoning Capabilities of Large Language Models

Ruibo Tu, Hedvig Kjellström, Gustav Eje Henter +1

Causal reasoning capabilities are essential for large language models (LLMs) in a wide range of applications, such as education and healthcare. But there is still a lack of benchma…

cs.HC2024★ 2 cited

Towards a GENEA Leaderboard -- an Extended, Living Benchmark for Evaluating and Advancing Conversational Motion Synthesis

Rajmund Nagy, Hendric Voss, Youngwoo Yoon +7

Current evaluation practices in speech-driven gesture generation lack standardisation and focus on aspects that are easy to measure over aspects that actually matter. This leads to…

cs.SD2024

Voice Conversion-based Privacy through Adversarial Information Hiding

Jacob J Webber, Oliver Watts, Gustav Eje Henter +2

Privacy-preserving voice conversion aims to remove only the attributes of speech audio that convey identity information, keeping other speech characteristics intact. This paper pre…

cs.SD2024

HiFi-Glot: High-Fidelity Neural Formant Synthesis with Differentiable Resonant Filters

Yicheng Gu, Pablo Pérez Zarazaga, Chaoren Wang +4

Formant synthesis aims to generate speech with controllable formant structures, enabling precise control of vocal resonance and phonetic features. However, while existing formant s…

eess.AS2024

Should you use a probabilistic duration model in TTS? Probably! Especially for spontaneous speech

Shivam Mehta, Harm Lameris, Rajiv Punmiya +3

Converting input symbols to output audio in TTS requires modelling the durations of speech sounds. Leading non-autoregressive (NAR) TTS models treat duration modelling as a regress…

cs.LG2024

Causality for Tabular Data Synthesis: A High-Order Structure Causal Benchmark Framework

Zineb Senane, Axel Karlsson, Lele Cao +6

Existing evaluations of tabular synthesis models rely primarily on low-order statistics and downstream task performance, leaving multivariate causal relationships that go beyond pa…

cs.HC2024

Fake it to make it: Using synthetic data to remedy the data shortage in joint multimodal speech-and-gesture synthesis

Shivam Mehta, Anna Deichler, Jim O'Regan +4

Although humans engaged in face-to-face conversation simultaneously communicate both verbally and non-verbally, methods for joint and unified synthesis of speech audio and co-speec…

cs.CL2024

Exploring Internal Numeracy in Language Models: A Case Study on ALBERT

Ulme Wennberg, Gustav Eje Henter

It has been found that Transformer-based language models have the ability to perform basic quantitative reasoning. In this paper, we propose a method for studying how these models…