ARTICLE lathoud06a/IDIAP Sector-Based Detection for Hands-Free Speech Enhancement in Cars Lathoud, Guillaume Bourgeois, Julien Freudenberger, Jürgen EXTERNAL http://publications.idiap.ch/attachments/papers/2006/lathoud06a.pdf PUBLIC http://publications.idiap.ch/index.php/publications/showcite/lathoud-rr-04-67 Related documents EURASIP Journal on Applied Signal Processing, Special Issue on Advances in Multimicrophone Speech Processing 2006 IDIAP RR 04-67 Adaptation control of beamforming interference cancellation techniques is investigated for in-car speech acquisition. Two efficient adaptation control methods are proposed that avoid target cancellation. The ``implicit'' method varies the step-size continuously, based on the filtered output signal. The ``explicit'' method decides in a binary manner whether to adapt or not, based on a novel estimate of target and interference energies. It estimates the average delay-sum power within a volume of space, for the same cost as the classical delay-sum. Experiments on real in-car data validate both methods, including a case with 100 km/h background road noise. REPORT lathoud-rr-04-67/IDIAP Sector-Based Detection for Hands-Free Speech Enhancement in Cars Lathoud, Guillaume Bourgeois, Julien Freudenberger, Jürgen EXTERNAL http://publications.idiap.ch/attachments/reports/2004/rr-04-67.pdf PUBLIC Idiap-RR-67-2004 2004 IDIAP Martigny, Switzerland Published in the EURASIP Journal on Applied Signal Processing, Special Issue on Advances in Multimicrophone Speech Processing Speech-based command interfaces are becoming more and more common in cars. Applications include automatic dialog systems for hands-free phone calls as well as more advanced features such as navigation systems. However, interferences, such as speech from the codriver, can hamper a lot the performance of the speech recognition component, which is crucial for those applications. This issue can be addressed with {\em adaptive} interference cancellation techniques such as the Generalized Sidelobe Canceller~(GSC). In order to cancel the interference (codriver) while not cancelling the target (driver,',','), adaptation must happen only when the interference is active and dominant. To that purpose, this paper proposes two efficient adaptation control methods called ``implicit'' and ``explicit''. While the ``implicit'' method is fully automatic, the ``explicit'' method relies on pre-estimation of target and interference energies. A major contribution of this paper is a direct, robust method for such pre-estimation, directly derived from sector-based detection and localization techniques. Experiments on real in-car data validate both adaptation methods, including a case with 100 km/h background road noise.