Adverse Conditions and ASR Techniques for Robust Speech User Interface
This addresses the challenge of making ASR systems more reliable for users in varied real-world conditions, but it appears to be an incremental review or discussion rather than presenting new empirical findings.
The paper tackles the problem of Automatic Speech Recognition (ASR) systems degrading in performance when acoustical environments differ between training and testing, aiming to increase robustness against environmental changes and speaker variations. It discusses difficulties and suggests techniques to compensate for these variations, but does not report specific experimental results or concrete numbers.
The main motivation for Automatic Speech Recognition (ASR) is efficient interfaces to computers, and for the interfaces to be natural and truly useful, it should provide coverage for a large group of users. The purpose of these tasks is to further improve man-machine communication. ASR systems exhibit unacceptable degradations in performance when the acoustical environments used for training and testing the system are not the same. The goal of this research is to increase the robustness of the speech recognition systems with respect to changes in the environment. A system can be labeled as environment-independent if the recognition accuracy for a new environment is the same or higher than that obtained when the system is retrained for that environment. Attaining such performance is the dream of the researchers. This paper elaborates some of the difficulties with Automatic Speech Recognition (ASR). These difficulties are classified into Speakers characteristics and environmental conditions, and tried to suggest some techniques to compensate variations in speech signal. This paper focuses on the robustness with respect to speakers variations and changes in the acoustical environment. We discussed several different external factors that change the environment and physiological differences that affect the performance of a speech recognition system followed by techniques that are helpful to design a robust ASR system.