Audio Signal Analysis
Listen to Understand
Sound is a wave made by vibration, that travels (typically) through air or another medium to our ear. Audio signals are representations of sounds in the form of signals whose frequencies are between the lower and upper limits of the human ears. With only in the human listening range, audio signals can have useful information.
Audio signal analysis is the basis of most of all audios-related research. The study can include extraction, interpretation, classification, etc. Once the information has been revealed the data can be processed for a logical, emotional, or other relevant interpretation depending on the domain of the research. With the power of our machine learning and deep learning technique, we have the ability to extract and process audio signals to match your requirements.
Data Corpus Engineering
Processing large amount of data into meaningful information
Development of AI-Tools
Design and create a useful tool for processing audio data
Feature Extraction
Preprocess and extract important features out of different data sources
Data Interpretation
Interpret significant and meaningful information from large amount of data
Successful Projects
AI-Traumatization Screening Tool
Development of a screening and support portal as an extensive psycho-social diagnostic mode for refugees
Automatic Detection of Affective Disorders
Features extraction of auditory, visual, and physiological data for diagnosis system of affective disorders
Pain Monitoring in Physiotherapy
Audio and facial expression based pain monitoring system
Driver State Monitoring for Autonomous Driving
Sudden sickness, distraction, and mind wondering detection by camera and audio based approaches for hand over situations in autonomous driving
Test Track Based ADAS Evaluation
Camera-Based Monitoring of Safety-Critical Driver Conditions
Test Track: Microsleep Intervention System
Evaluation of multiple fatigue intervention systems
Advanced Driver Assistance System: Mental Workload Detection
Multimodal physiological measurements of mental workload for evaluating ADAS
EEG, Speech, and Video-Based Vigilance Detection
Multimodal hypovigilance measures
Robot Learning Assistant for Children with ASD
Computer vision-based detection of attention
Virtual Coach for Smart Ageing
Developing of emphatic dialog systems: an EU-Japanese collaboration