Time- and spectrum-related variabilities in stressed speech under laboratory and real conditions
Speech Communication - Special issue on speech under stress
Speech Communication - Special issue on speech under stress
Modeling drivers' speech under stress
Speech Communication - Special issue on speech and emotion
Benchmarking Attribute Selection Techniques for Discrete Class Data Mining
IEEE Transactions on Knowledge and Data Engineering
Unsupervised word sense disambiguation rivaling supervised methods
ACL '95 Proceedings of the 33rd annual meeting on Association for Computational Linguistics
Real-time discrimination of broadcast speech/music
ICASSP '96 Proceedings of the Acoustics, Speech, and Signal Processing, 1996. on Conference Proceedings., 1996 IEEE International Conference - Volume 02
Speech Under Stress: Analysis, Modeling and Recognition
Speaker Classification I
EmotionSense: a mobile phones based adaptive platform for experimental social psychology research
Proceedings of the 12th ACM international conference on Ubiquitous computing
Some useful properties of Teager's energy operators
ICASSP'93 Proceedings of the 1993 IEEE international conference on Acoustics, speech, and signal processing: digital speech processing - Volume III
SpeakerSense: energy efficient unobtrusive speaker identification on mobile phones
Pervasive'11 Proceedings of the 9th international conference on Pervasive computing
Poster abstract: a mobile-cloud service for physiological anomaly detection on smartphones
Proceedings of the 12th international conference on Information processing in sensor networks
Auditeur: a mobile-cloud service platform for acoustic event detection on smartphones
Proceeding of the 11th annual international conference on Mobile systems, applications, and services
Proceedings of the 2013 ACM international joint conference on Pervasive and ubiquitous computing
NLify: lightweight spoken natural language interfaces via exhaustive paraphrasing
Proceedings of the 2013 ACM international joint conference on Pervasive and ubiquitous computing
Predicting audience responses to movie content from electro-dermal activity signals
Proceedings of the 2013 ACM international joint conference on Pervasive and ubiquitous computing
iSleep: unobtrusive sleep quality monitoring using smartphones
Proceedings of the 11th ACM Conference on Embedded Networked Sensor Systems
Multimodal analysis of body communication cues in employment interviews
Proceedings of the 15th ACM on International conference on multimodal interaction
Sensor-less sensing for affective computing and stress management technology
Proceedings of the 7th International Conference on Pervasive Computing Technologies for Healthcare
Sensing stress network for social coping
Proceedings of the companion publication of the 17th ACM conference on Computer supported cooperative work & social computing
Sinabro: opportunistic and unobtrusive mobile electrocardiogram monitoring system
Proceedings of the 15th Workshop on Mobile Computing Systems and Applications
ipShield: a framework for enforcing context-aware privacy
NSDI'14 Proceedings of the 11th USENIX Conference on Networked Systems Design and Implementation
| Hi-index | 0.00 |
Stress can have long term adverse effects on individuals' physical and mental well-being. Changes in the speech production process is one of many physiological changes that happen during stress. Microphones, embedded in mobile phones and carried ubiquitously by people, provide the opportunity to continuously and non-invasively monitor stress in real-life situations. We propose StressSense for unobtrusively recognizing stress from human voice using smartphones. We investigate methods for adapting a one-size-fits-all stress model to individual speakers and scenarios. We demonstrate that the StressSense classifier can robustly identify stress across multiple individuals in diverse acoustic environments: using model adaptation StressSense achieves 81% and 76% accuracy for indoor and outdoor environments, respectively. We show that StressSense can be implemented on commodity Android phones and run in real-time. To the best of our knowledge, StressSense represents the first system to consider voice based stress detection and model adaptation in diverse real-life conversational situations using smartphones.