Recognition of Reverberant Speech Using Frequency Domain Linear Prediction

Linear prediction modulation filtering for speaker recognition of reverberant speech

This paper proposes a framework for spectral enhancement of reverberant speech based on inversion of the modulation transfer function. All-pole modeling of modulation spectra of clean and degraded speech are utilized to derive the linear prediction inverse modulation transfer function (LP-IMTF) solution as a low-order IIR filter in the modulation envelope domain. By considering spectral estimat...

Frequency Domain Linear Prediction for Speech and Audio Applications

Front-end for far-field speech recognition based on frequency domain linear prediction

Automatic Speech Recognition (ASR) systems usually fail when they encounter speech from far-field microphone in reverberant environments. This is due to the application of short-term feature extraction techniques which do not compensate for the artifacts introduced by long room impulse responses. In this paper, we propose a front-end, based on Frequency Domain Linear Prediction (FDLP), that tri...

Dynamic features in the linear domain for robust automatic speech recognition in a reverberant environment

Since the MFCC are calculated from logarithmic spectra, the delta and delta-delta are considered as difference operations in a logarithmic domain. In a reverberant environment, speech signals have trailing reverberations, whose power is plotted as a long-term exponential decay. This means the logarithmic delta value tends to remain large for a long time. This paper proposes a delta feature calc...

Acoustic Model Adaptation Using First-Order Linear Prediction for Reverberant Speech

This paper describes a hands-free speech recognition technique based on acoustic model adaptation to reverberant speech. In handsfree speech recognition, the recognition accuracy is degraded by reverberation, since each segment of speech is affected by the reflection energy of the preceding segment. To compensate for the reflection signal we introduce a frame-by-frame adaptation method adding t...