The accuracy of automatic speech recognizer degrades rapidly when speech was distorted by noise. Robustness against noise arises to be one of the challenge problems. In this paper, a hidden Markov model (HMM) based data imputation approach is presented to improve speech recognition robustness against noise at the front-end of recognizer. Considering the correlation between different filter-bank...

In this paper we present recent results on the development of the SynFace lip synchronized talking head towards multilinguality, varying signal conditions and noise robustness in the Hearing at Home project. We then describe the large scale hearing impaired user studies carried out for three languages. The user tests focus on measuring the gain in Speech Reception Threshold in Noise when using ...

The emerging applications of speech technology especially in the fields of wireless applications, digital hearing aids or speech recognition are often requiring a noise reduction technique in combination with a precise Voice Activity Detector (VAD). In this paper, we compare the performance of the VAD algorithms like Zero Crossing Detection(ZCD), Weak Fricative Detection (WFD), Pitch Based Dete...

This article describes the development of a test for measuring the intelligibility of speech in noise for the Spanish language, similar to the test developed by Kalikow, Stevens, and Elliot (Journal of the Acoustical Society of America, 5, 1337-1360, 1977) for the English language. The test consists of six forms, each comprising 25 high-predictability (HP) sentences and 25 low-predictability (L...

A two-part study examined recognition of speech produced in quiet and in noise by normal hearing adults. In Part I 5 women produced 50 sentences consisting of an ambiguous carrier phrase followed by a unique target word. These sentences were spoken in three environments: quiet, wide band noise (WBN), and meaningful multi-talker babble (MMB). The WBN and MMB competitors were presented through in...

Difficulty communicating in noise is a common complaint for people with hearing loss. When communicating in noise, speakers increase the intensity level of their voice and alter the stress patterns of their speech not only to monitor their own voice but also to be heard by others. Speech that increases in intensity for the purpose of self-monitoring and being understood in noise is called Lomba...

It is very important to detect the speech endpoints accurately in speech recognition. This paper presents a comparative analysis of various feature extraction techniques of endpoint detection in speech recognition of isolated words in noisy environments. The endpoint detection problem is nontrivial for no stationary backgrounds where artifacts (i.e., no speech events) may be introduced by the s...

A speech enhancement algorithm is proposed that exploits the masking properties of the human auditory system. The enhancement is formulated as a frequency domain constrained optimization problem. The noise components of the noisy speech are suppressed by a gain function subject to the constraint that both the signal distortion and residual noise should fall below the masking thresholds. Tempora...

The potential contribution of the peripheral auditory efferent system to our understanding of speech in a background of competing noise was studied using a computer model of the auditory periphery and assessed using an automatic speech recognition system. A previous study had shown that a fixed efferent attenuation applied to all channels of a multi-channel model could improve the recognition o...