Signal Processing and Speech Communication Laboratory
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Research Programs and Projects

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2023 — 2029 Christian Doppler Laboratory for Dependable Intelligent Systems in Harsh Environments

In industry, data-driven techniques have revolutionized manufacturing by collecting huge amounts of information during production and turning it into valuable information for process optimization. While machine learning (ML) is a key technology and the main contributing factor for many recent success stories, we witness the transition of ML moving from the “virtual world” into “the wild”; this includes prominent applications in autonomous navigation, the Internet of Things, and Industry 4.0 applications. Evidently, this transition opens several real-world challenges for ML that need to be addressed for closing the gap between both worlds.
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2019 — 2025 Christian Doppler Laboratory for Location-aware Electronic Systems

The Christian Doppler Laboratory for Location-Aware Electronic Systems has the long-term vision of investigating fundamental limitations of location-aware electronic systems and creating and validating key algorithm solutions and transducer hardware designs for it.
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2015 — ongoing Common Language Resources and Technology Infrastructure

CLARIN is the Common Language Resources and Technology Infrastructure, which provides easy and sustainable access for scholars in the humanities and social sciences to digital language data (in written, spoken, video or multimodal form), and advanced tools to discover, explore, exploit, annotate, analyse or combine them, wherever they are located. CLARIN is building a networked federation of language data repositories, service centres and centres of expertise, with single sign-on access for all members of the academic community in all participating countries. Tools and data from different centres are interoperable, so that data collections can be combined and tools from different sources can be chained to perform complex operations to support researchers in their work.
2025 — 2029 Voice conversion for the processing of pathological speech (FWF Stand-Alone Project PAT5948223)

Impaired speech production poses significant communication hurdles, often impacting career prospects and quality of life. This project envisions (i) the prediction of effects of clinical treatment of impaired speech, and (ii) a better sounding substitution speech, i.e., electrolarynx (EL) speech, for individuals with otherwise unfavorable prospects.

Objectives:

Objective 1 is to predict post-treatment speech audio recordings, i.e., readings of a German standard text. Input data is paired text-parallel pre-treatment speech audio recordings, and electronic patient records (EPRs), i.e., unstructured textual clinical reports containing information about the speech impairment and treatment plan.

Objective 2 is to improve speech of larygectomees in...
2025 — 2028 PRISM - Perceptive Radar Induction via Symbolic Modeling

Recent advances in sensor technology have paved the way for multi-sensor systems to become a practical and cost-effective solution across a range of industries, including mobile radio systems, energy grids, and autonomous vehicles. These systems improve perception, reliability, and robustness by integrating diverse sensors; however, they introduce new challenges regarding effective joint processing. Traditional multi-sensor processing methods rely either on classical analytical techniques or purely data-driven approaches, such as deep learning. While analytical methods may miss crucial data from individual sensors, data-driven models require large volumes of high-quality data and often lack interpretability. Achieving coherent multi-sensor processing requires overcoming environmental...
2016 — 2026 PipeSense

Gas pipelines and power lines are part of the critical civil infrastructure of a country. Fibre Optic Monitoring of linear distribution infrastructure is done using Distributed Acoustic Sensing (DAS). New methods of pipeline monitoring are developed and evaluated in field trials.
2022 — 2026 Hybrid20 - Fundamentals for integrated computational material, process and product engineering

The core objective of the project Hybrid20 is to establish at the center viable methods for construction of probabilistic hybrid semiparametric models of physical systems (including materials, production processes or products in operation) and to document their applicability in four Use-Cases. Hybrid semiparametric models combine knowledge (parametric sub-models) and observation (nonparametric sub-models). Probabilistic hybrid models treat some of their variables as random variables. We require their outputs to provide distributions rather than point estimates (output variables as random variables). Distributions allow for derivation of output confidence metrics, which is the key requirement to establish trust and further use of complex...

Finished Programs

Finished Projects