Speaker identification and verification using Gaussian mixture speaker models
Speech Communication
Towards a definition and working model of stress and its effects on speech
Speech Communication - Special issue on speech under stress
Speech Communication - Special issue on speech under stress
Workload and the use of automatic speech recognition: the effects of time and resource demands
Speech Communication - Special issue on speech under stress
Classification of speech under stress using target driven features
Speech Communication - Special issue on speech under stress
Speech Communication - Special issue on speech under stress
Emotions, speech and the ASR framework
Speech Communication - Special issue on speech and emotion
CBMS '95 Proceedings of the Eighth Annual IEEE Symposium on Computer-Based Medical Systems
Speaker understandability as a function of prosodic parameters
Speaker understandability as a function of prosodic parameters
Analysis, modeling and perturbation of speech under stress with applications to speech synthesis and recognition
Multi-expert automatic speech recognition system using myoelectric signals
Multi-expert automatic speech recognition system using myoelectric signals
Wearable Data Aquisition for Heartbeat and Respiratory Information
ISWC '05 Proceedings of the Ninth IEEE International Symposium on Wearable Computers
Improved speech recognition via speaker stress directed classification
ICASSP '96 Proceedings of the Acoustics, Speech, and Signal Processing, 1996. on Conference Proceedings., 1996 IEEE International Conference - Volume 01
Automatic speech recognition and speech variability: A review
Speech Communication
A tutorial on text-independent speaker verification
EURASIP Journal on Applied Signal Processing
Dialect/Accent Classification Using Unrestricted Audio
IEEE Transactions on Audio, Speech, and Language Processing
Exploiting nonacoustic sensors for speech encoding
IEEE Transactions on Audio, Speech, and Language Processing
IEEE Journal on Selected Areas in Communications
Speech Communication
Paralinguistics in speech and language-State-of-the-art and the challenge
Computer Speech and Language
Ten recent trends in computational paralinguistics
COST'11 Proceedings of the 2011 international conference on Cognitive Behavioural Systems
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Interactive speech system scenarios exist which require the user to perform tasks which exert limitations on speech production, thereby causing speaker variability and reduced speech performance. In noisy stressful scenarios, even if noise could be completely eliminated, the production variability brought on by stress, including Lombard effect, has a more pronounced impact on speech system performance. Thus, in this study we focus on the use of a silent speech interface (PMIC), with a corresponding experimental assessment to illustrate its utility in the tasks of stress detection and speaker verification. This study focuses on the suitability of PMIC versus close-talk microphone (CTM), and reports that the PMIC achieves as good performance as CTM or better for a number of test conditions. PMIC reflects both stress-related information and speaker-dependent information to a far greater extent than the CTM. For stress detection performance (which is reported in % accuracy), PMIC performs at least on par or about 2% better than the CTM-based system. For a speaker verification application, the PMIC outperforms CTM for all matched stress conditions. The performance reported in terms of %EER is 0.91% (as compared to 1.69%), 0.45% (as compared to 1.49%), and 1.42% (as compared to 1.80%) for PMIC. This indicates that PMIC reflects speaker-dependent information. Also, another advantage of the PMIC is its ability to record the user physiology traits/state. Our experiments illustrate that PMIC can be an attractive alternative for stress detection as well as speaker verification tasks along with an advantage of its ability to record physiological information, in situations where the use of CTM may hinder operations (deep sea divers, fire-fighters in rescue operations, etc.).