In-Car speech recognition will be pervasive over the coming years. The goal of speech enhancement is to increase the quality and intelligibility of speech in a noisy environment. The focus of the present research is to evaluate the effect of speech enhancement on the intelligibility of spoken language in a moving vehicle. Here, an ECoS network is used as a model to evaluate the intelligibility....

Speech enhancement employing Deep Neural Networks (DNNs) is gaining strength as a data-driven alternative to classical Minimum Mean Square Error (MMSE) enhancement approaches. In the past, Observation Uncertainty approaches to integrate MMSE speech enhancement with Automatic Speech Recognition (ASR) have yielded good results as a lightweight alternative for robust ASR. In this paper we thus exp...

Text-to-speech (TTS) synthesis systems have grown popularity due to their diverse practical usability. While most of the technologies developed aims to meet requirements in laboratory environment, the practical appliance is not limited to a specific environment. This work aims towards improving intelligibility of synthesized speech to make it deployable in realism. Based on the comparison of Lo...

This work presents an approach to speech enhancement that operates using a speech production model to reconstruct a clean speech signal from a set of speech parameters that are estimated from the noisy speech. The motivation is to remove the distortion and residual and musical noises that are associated with conventional filtering-based methods of speech enhancement. The STRAIGHT vocoder forms ...

We address issues for improving hands-free speech enhancement and speech recognition performance in different car environments using a single distant microphone. This paper describes a new singlechannel in-car speech enhancement method that estimates the log spectra of speech at a close-talking microphone based on the nonlinear regression of the log spectra of noisy signal captured by a distant...

The goal of this paper is to perform a performance analysis for speech enhancement using classical adaptive filters with kalman filter. In many applications like speech recognition, hearing aids, forensic applications and telephone conversations etc... As the enhancement of speech signals is of very important. The performance of the speech recognition system is also reduces if the speech signal...

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...

The performance of two-microphone coherence based methods degrades if two captured noises are correlated. The Cross Power Spectrum Subtraction (CPSS) is an adapted coherence method for noise correlated environments. In this paper, we propose a new technique for estimation of speech cross power spectrum density and we exploit it in CPSS. The proposed speech enhancement method is evaluated as a s...

This paper presents a new approach to single-channel speech enhancement involving both noise and channel distortion (i.e., convolutional noise). The approach is based on finding longest matching segments (LMS) from a corpus of clean, wideband speech. The approach adds three novel developments to our previous LMS research. First, we address the problem of channel distortion as well as additive n...