34 citations · 47 across the 6 of their papers we have counts for
7 papers
Detecting Vocal Fatigue with Neural Embeddings
Sebastian P. Bayerl, Dominik Wagner, Ilja Baumann +2
Vocal fatigue refers to the feeling of tiredness and weakness of voice due to extended utilization. This paper investigates the effectiveness of neural embeddings for the detection…
Detecting Emotion Carriers by Combining Acoustic and Lexical Representations
Sebastian P. Bayerl, Aniruddha Tammewar, Korbinian Riedhammer +1
Personal narratives (PN) - spoken or written - are recollections of facts, people, events, and thoughts from one's own experience. Emotion recognition and sentiment analysis tasks…
STAN: A stuttering therapy analysis helper
Sebastian P. Bayerl, Marc Wenninger, Jochen Schmidt +2
Stuttering is a complex speech disorder identified by repeti-tions, prolongations of sounds, syllables or words and blockswhile speaking. Specific stuttering behaviour differs stro…
Offline Model Guard: Secure and Private ML on Mobile Devices
Sebastian P. Bayerl, Tommaso Frassetto, Patrick Jauernig +5
Performing machine learning tasks in mobile applications yields a challenging conflict of interest: highly sensitive client information (e.g., speech data) should remain private wh…
Towards Automated Assessment of Stuttering and Stuttering Therapy
Sebastian P. Bayerl, Florian Hönig, Joelle Reister +1
Stuttering is a complex speech disorder that can be identified by repetitions, prolongations of sounds, syllables or words, and blocks while speaking. Severity assessment is usuall…
A Comparison of Hybrid and End-to-End Models for Syllable Recognition
Sebastian P. Bayerl, Korbinian Riedhammer
This paper presents a comparison of a traditional hybrid speech recognition system (kaldi using WFST and TDNN with lattice-free MMI) and a lexicon-free end-to-end (TensorFlow imple…
Timage -- A Robust Time Series Classification Pipeline
Marc Wenninger, Sebastian P. Bayerl, Jochen Schmidt +1
Time series are series of values ordered by time. This kind of data can be found in many real world settings. Classifying time series is a difficult task and an active area of rese…