| ANIR Corpus |
 The "ANIR" (Automotive Noise and Impulse Responses) corpus allows investigating automotive speech and audio processing. Currently, impulse responses are measured from different sources (mouth loudspeakers, car loudspeakers) to different sinks (ear microphones, in-car microphones). Additionally, several driving conditions (standstill, slow and fast speed) are recorded in terms of noise examples. Details ... |
| MuMoSD Corpus |
 The "MuMoSD" (MultiModal Swallowing Detection) corpus is a database that contains various signals from volunteers performing different tasks, including swallowing. Swallowing issues can lead to choking, coughing, nasal regurgitation, pain, malnutrition, and more. This is why developing techniques for analyzing swallowing is crucial for early symptom detection. MuMoSD includes tasks such as swallowing different liquids, coughing, and speech, recorded using various sensors. Details ... |
| SPID Corpus |
 The "SPID" (SPontaneous In-car Dialogues) corpus allows investigating - for the first time ever - the communication between speakers inside a driving car and the Lombard effect that emerges at different driving speeds. Currently, speech recordings are made in order to analyze the effects of an in-car-communication (ICC) system on speech production at different driving noise levels. Details ... |
| SUMS Corpus |
 The "SUMS" (Speech Under Multiple Stressors) corpus allows investigating the effects of multiple stressors to speech. This corpus addresses the questions on which basis and in which way all the different stress types shine through and combine in the acoustic speech signal. We used several stressors that form a taxonomy of stress factors. Pink noise served as an external stressor. A further stress factor, cognitive load, was created by asking quiz questions. Details ... |
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