Simultaneous Blind Separation and Recognition of Speech Mixtures Using Two Microphones to Control a Robot Cleaner

Abstract

This paper proposes a method for the simultaneous separation and recognition of speech mixtures in noisy environments using two-channel based independent vector analysis (IVA) on a home-robot cleaner. The issues to be considered in our target application are speech recognition at a distance and noise removal to cope with a variety of noises, including TV sounds, air conditioners, babble, and so on, that can occur in a house, where people can utter a voice command to control a robot cleaner at any time and at any location, even while a robot cleaner is moving. Thus, the system should always be in a recognition-ready state to promptly recognize a spoken word at any time, and the false acceptance rate should be lower. To cope with these issues, the keyword spotting technique is applied. In addition, a microphone alignment method and a model-based real-time IVA approach are proposed to effectively and simultaneously process the speech and noise sources, as well as to cover 360-degree directions irrespective of distance. From the experimental evaluations, we show that the proposed method is robust in terms of speech recognition accuracy, even when the speaker location is unfixed and changes all the time. In addition, the proposed method shows good performance in severely noisy environments.