This study examined changes in rhythmic arm shaking and laterality biases in infants observed longitudinally at three points: just prior to, at, and just following reduplicated babble onset. Infants (ranging in age from 4 to 9 months at babble onset) were videotaped at home as they played with two visually identical audible and silent rattles presented at midline for 1.5 min each. Rate of rattl...

An auditory model based on zero-crossings with peak amplitudes (ZCPA) was used as a front-end for automatic speech recognition (ASR) with the perceptual property of adaptation as determined by psychoacoustic observations. The model performance was evaluated on the isolated digits (TIDIGITS) database using continuous density HMM recognizer in additive noise. Experimental results indicate that th...

Numerous efforts have focused on the problem of reducing the impact of noise on the performance of various speech systems such as speech recognition, speaker recognition, and speech coding. These approaches consider alternative speech features, improved speech modeling, or alternative training for acoustic speech models. This study presents an alternative viewpoint by approaching the same probl...

"Listening systems" are used for hearing impaired listeners as an alternative to public address systems (PA) used for the general public. These listening systems allow individual control of sound pressure level and minimize the effects of background noise and room reverberation. Three listening systems, based on an audio induction loop (AL), frequency modulation of radio frequencies (FM), and m...

Communication success under adverse conditions requires efficient and effective recruitment of both bottom-up (sensori-perceptual) and top-down (cognitive-linguistic) resources to decode the intended auditory-verbal message. Employing these limited capacity resources has been shown to vary across the lifespan, with evidence indicating that younger adults out-perform older adults for both compre...

This paper proposes a novel model composition method to improve speech recognition performance in time-varying background noise conditions. It is suggested that each order of the cepstral coefficients represents the frequency degree of changing components in the envelope of the log-spectrum. With this motivation, in the proposed method, variational noise models are generated by selectively appl...

The present study (1) assessed the reliability of the acceptable noise level (ANL) measure using speech-spectrum and speech-babble noises as the competing stimuli, and (2) investigated the relationship between ANL and preference for background sounds in 30 young adults with normal hearing sensitivity. Listeners were evaluated during three test sessions approximately one week apart. Results demo...

This paper examines the effectiveness of a generalized dynamic cepstrum in distant speech recognition. The generalized dynamic cepstrum (DyMFGC) is based upon the forward masking on the generalized logarithmic spectrum instead of the log-spectrum, which intends to make it robust to additive noise as well as convolutional noise. Digit recognition tests were carried out in a relatively quiet and ...

Automatic Speech Recognition Systems of today are intensely deployed in real world application scenarios which are often characterized by suboptimal operating conditions. Thus their noise robustness has become a crucial parameter when assessing ASR in-field performance. The paper examines the noise robustness of traditional ASR feature sets as applied to a Voice Dialing Application built for Ma...

In this paper, we investigate the noise robustness properties of frame-based and sparse point process-based models for spotting keywords in continuous speech. We introduce a new strategy to improve point process model (PPM) robustness by adapting low-level feature detector thresholds to preserve background firing rates in the presence of noise. We find that this unsupervised approach can signif...