Join us on Aug 6 for a special edition of the AI, ML, and Computer Vision Meetup focused on audio use cases!
Date, Time and Location
Aug 06, 2026
9:00 AM - 11:00 AM PST
Online. Register for the Zoom
Do Speech Models Actually Understand Speech? Evaluating Speech LLMs Under Realistic Spoken Instruction Conditions
Speech Large Language Models (SLLMs) are increasingly capable; but are we evaluating them the right way? Most benchmarks rely on text prompts, yet real users interact with these systems through speech, a modality that introduces noise, disfluencies, and stylistic variation that text simply doesn't capture.
In this talk, we present findings from a systematic study across 11 tasks, 12 languages, and five prompt styles, examining how prompt modality, language, and task type shape SLLM performance.
About the Speaker
Maike Züfle is a PhD student at the Karlsruhe Institute of Technology (KIT), working in Prof. Jan Niehues's group on interactive speech systems for more natural human–machine communication.
AI based Audio Forensics
In this presentation, attendees will discover several modules developed by Gradiant for the detection and analysis of synthetically generated or manipulated audio. The session will be delivered by one of the developers involved in the design and implementation of these technologies, providing first-hand insight into their capabilities and underlying methodology.
The presentation will cover the traceability module, which helps identify the origin of AI-generated content. It will also cover the segment detection tool, designed to locate manipulated regions within an audio recording, as well as the complete audio detection tool, which assesses whether an entire recording has been synthetically generated.
About the Speaker
Daniel Paniagua Ares is a research engineer at Gradiant. Graduated in computer engineering from the FIC and with a master's degree in AI from the VIU.
Curating, Searching, and Evaluating Audio Datasets in FiftyOne