Increasing Speech Recognition Noise Robustness with HMM2
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This report presents the integration of several noise reduction methods into the front-end for speech recognition developed at IDIAP. The chosen methods are : Spectral Subtraction, Cepstral Mean Subtraction and Blind Equalization. These different methods a ...
This paper is a report for the Postgraduate course Language and Speech Engineering. The report describes the part work of InfoVOX project, the goal is to implement Speech Recognition Engine (SRE) on Windows with state-of-the-art SR technologies, and integr ...
The challenge of automatic speech recognition (ASR) increases when speaker variability is encountered. Being able to automatically use different acoustic models according to speaker type might help to increase the robustness of ASR. We present a system tha ...
In this report, we discuss the initial issues addressed in a research project aiming at the development of an advanced natural speech recognition system for the automatic processing of telephone directory requests. This multi-faceted project involves (1) t ...
