Getting start with UTDrive: driver-behavior modeling and assessment of distraction for in-vehicle speech systems

This paper describes our first step for advances in humanmachine interactive systems for in-vehicle environments of the UTDrive project. UTDrive is part of an on-going international collaboration to collect and research rich multi-modal data recorded for modeling behavior while the driver is interacting with speech-activated systems or performing other secondary tasks. A simultaneous second goal is to better understand speech characteristics of the driver undergoing additional cognitive load since dialog systems are generally not formulated for high task-stress environment (e.g., driving a vehicle). The corpus consists of audio, video, brake/gas pedal pressure, forward distance, GPS information, and CAN-Bus information. The resulting corpus, analysis, and modeling will contribute to more effective speech systems which are able to sense driver cognitive distraction/stress and adapt itself to the driver’s cognitive capacity and driving situations for improved safety while driving.

[1]  Kazuya Takeda,et al.  Driver Recognition System Using FNN and Statistical Methods , 2007 .

[2]  Harry Wechsler,et al.  Modeling and Prediction , 2007 .

[3]  John H. L. Hansen,et al.  Analysis and compensation of speech under stress and noise for environmental robustness in speech recognition , 1996, Speech Commun..

[4]  Bhiksha Raj,et al.  A Comparison Between Spoken Queries and Menu-Based Interfaces for In-car Digital Music Selection , 2005, INTERACT.

[5]  Hakan Erdogan,et al.  Multi-modal Person Recognition for Vehicular Applications , 2005, Multiple Classifier Systems.

[6]  Paul Green,et al.  Safety and Usability of Speech Interfaces for In-Vehicle Tasks while Driving: A Brief Literature Review , 2006 .

[7]  John H. L. Hansen,et al.  Audio-visual SPeaker localization for car navigation systems , 2004, INTERSPEECH.

[8]  Alex Pentland,et al.  Modeling and Prediction of Human Behavior , 1999, Neural Computation.

[9]  Hong-Seok Kim,et al.  Performance of an HMM speech recognizer using a real-time tracking microphone array as input , 1999, IEEE Trans. Speech Audio Process..

[10]  Mikko Sams Audio-visual speech processing and attention , 2003 .

[11]  Robert Graham,et al.  Experimental Comparison of Manual and Voice Controls for the Operation of in-Vehicle Systems , 2000 .

[12]  John H. L. Hansen,et al.  CSA-BF: a constrained switched adaptive beamformer for speech enhancement and recognition in real car environments , 2003, IEEE Trans. Speech Audio Process..

[13]  John H. L. Hansen,et al.  "CU-move": robust speech processing for in-vehicle speech systems , 2000, INTERSPEECH.

[14]  Kazuya Takeda,et al.  Driver Modeling Based on Driving Behavior and Its Evaluation in Driver Identification , 2007, Proceedings of the IEEE.