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Cochlear implant (CI) recipients require alternative signal processing for speech enhancement, since the quantities needed for intelligibility and quality improvement differ significantly when direct stimulation of the basilar membrane is employed for CIs. Here, a robust feature vector is proposed for environment classification in CI devices. The feature vector is directly computed from the output...
Robustness of speaker recognition systems is crucial for real-world applications, which typically contain both additive noise and room reverberation. However, the combined effects of additive noise and convolutive reverberation have been rarely studied in speaker identification (SID). This paper addresses this issue in two phases. We first remove background noise through binary masking using a deep...
This work presents an analysis of distant-talking speech recognition in a variety of reverberant conditions, correlating ASR performance to the acoustic characteristics of a given propagation channel. In particular we show how, for a digit recognition task, the ASR accuracy is directly related to the Early-to-Late Reverberation ratio of the room impulse response, capturing in a single parameter the...
This work analyzes the influence of reverberation on automatic speech recognition (ASR) systems and how to compensate its influence, with special focus on the important acoustical parameters i.e. room reverberation time T60 and clarity index C50. A multilayer perceptron (MLP) using features of a spectro-temporal filter bank as input is employed to identify the acoustic conditions spanning various...
Over the past few decades, a range of front-end techniques have been proposed to improve the robustness of automatic speech recognition systems against environmental distortion. While these techniques are effective for small tasks consisting of carefully designed data sets, especially when used with a classical acoustic model, there has been limited evidence that they are useful for a state-of-the-art...
This paper investigates an implication of the clustering, on the complex plane, of the roots of transfer function polynomials obtained from acoustic responses. These polynomials can be the high order transfer functions obtained from room impulse responses or the relatively lower order ones obtained from head related impulse responses. This clustering behavior is explained using results from the theory...
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