Objectives: To identify and assess the level of development of motor abilities in older pre-school -age children with speech disorder. Methods: The study included 200 older pre-school age children, 100 children with a healthy level of speech development and 100 with speech disorder, in Belgorod and Belgorod region (Russian Federation). The study looked at scientific sources; motor abilities te...

Speaker and task adaptation can be made more efficient if an automatic speech recognition system can actively elicit particularly useful adaptation data from a new speaker for a given speech recognition task. This paper presents such an active approach based on an automatic analysis of how difficult the given task vocabulary is. Comparative experiments are designed and conducted for a simple ap...

In this paper an estimator for speech enhancement based on Laplacian Mixture Model has been proposed. The proposed method, estimates the complex DFT coefficients of clean speech from noisy speech using the MMSE  estimator, when the clean speech DFT coefficients are supposed mixture of Laplacians and the DFT coefficients of  noise are assumed zero-mean Gaussian distribution. Furthermore, the MMS...

It is common for subjects to produce speech while performing a physical task where speech technology may be used. Variabilities are introduced to speech since physical task can influence human speech production. These variabilities degrade the performance of most speech systems. It is vital to detect speech under physical stress variabilities for subsequent algorithm processsing. This study pre...

Distant speech recognition is a highly challenging task due to background noise, reverberation, and speech overlap. Recently, there has been an increasing focus on attention mechanism. In this paper, we explore the attention mechanism embedded within the long short-term memory (LSTM) based acoustic model for large vocabulary distant speech recognition, trained using speech recorded from a singl...

Generalization is a common issue for automatic speech recognition. A successful method used to improve recognition results consists of training a single system to solve multiple related tasks in parallel. This overview investigates which auxiliary tasks are helpful for speech recognition when multi-task learning is applied on a deep learning based acoustic model. The impact of multi-task learni...

background: previous studies have shown that interaural-time-difference (itd) training can improve localization ability. surprisingly little is, however, known about localization training vis-à-vis speech perception in noise based on interaural time difference in the envelope (itd env). we sought to investigate the reliability of an itd env-based training program in speech-in-noise perception a...