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Form about four decades human beings have been dreaming of an intelligentmachine which can master the natural speech. In its simplest form, this machineshould consist of two subsystems, namely automatic speech recognition (ASR) andspeech understanding (SU). The goal of ASR is to transcribe natural speechwhile SU is to understand the meaning of the transcription. Recognizing andunderstanding a spoken sentence is obviously a knowledge-intensive process,which must take into account all variable information about the speechcommunication process, from acoustics to semantics and pragmatics. Whiledeveloping an Automatic Speech Recognition System, it is observed that someadverse conditions degrade the performance of the Speech Recognition System. Inthis contribution, speech enhancement system is introduced for enhancing speechsignals corrupted by additive noise and improving the performance of AutomaticSpeech Recognizers in noisy conditions. Automatic speech recognitionexperiments show that replacing noisy speech signals by the correspondingenhanced speech signals leads to an improvement in the recognition accuracies.The amount of improvement varies with the type of the corrupting noise.

Speech Enhancement Modeling Towards Robust Speech Recognition System