6 accepted papers
Video summarization aims to generate a condensed textual version of an original video. Summaries may consist of either plain text or a shortlist of salient events, possibly including temporal or spatial references. Video Large Language Models (VLLMs) exhibit impressive zero-shot capabilities in vide…
Speech foundation models have demonstrated exceptional capabilities in speech-related tasks. Nevertheless, these models often struggle with non-verbal audio data, such as vocalizations, baby crying, etc., which are critical for various real-world applications. Audio foundation models well handle non…
In the domain of music generation, prevailing methods focus on text-to-music tasks, predominantly relying on diffusion models. However, they fail to achieve good vocal quality in synthetic music compositions.To tackle this critical challenge, we present Ainur, a hierarchical diffusion model that con…
As speech processing moves toward more data-hungry models, data selection and acquisition become crucial to building better systems. Recent efforts have championed quantity over quality, following the mantra "The more data, the better." However, not every data brings the same benefit. This paper pro…
Italy exhibits rich linguistic diversity across its territory due to the distinct regional languages spoken in different areas. Recent advances in self-supervised learning provide new opportunities to analyze Italy’s linguistic varieties using speech data alone. This includes the potential to levera…
End-to-End Spoken Language Understanding models are generally evaluated according to their overall accuracy, or separately on (a priori defined) data subgroups of interest. We propose a technique for analyzing model performance at the subgroup level, which considers all subgroups that can be defined…