Major progress is being recorded regularly on both the technology and exploitation of
automatic speech recognition (ASR) and spoken language systems. However, there are still …

This paper describes a speech recognition system that uses both acoustic and visual
speech information to improve recognition performance in noisy environments. The system …

The major challenge that faces American Sign Language (ASL) recognition now is
developing methods that will scale well with increasing vocabulary size. Unlike in spoken …

The major challenge that faces American Sign Language (ASL) recognition now is to
develop methods that will scale well with increasing vocabulary size. Unlike in spoken …

The most popular systems for automatic sign language recognition are based on vision.
They are user-friendly, but very sensitive to changes in regard to recording conditions. This …

Whereas most state-of-the-art speech recognition systems use spectral or cepstral
representations of the speech signal, there have also been some promising attempts at …

The acoustic-phonetic modeling component of most current speech recognition systems
calculates a small set of homogeneous frame-based measurements at a single, fixed time …

In this paper we propose a new feature vector consisting of mel-frequency discrete wavelet
coefficients (MFDWC). The MFDWC are obtained by applying the discrete wavelet transform …

In this paper, we present a multi-stream approach for off-line handwritten word recognition.
The proposed approach combines low level feature streams namely, density based features …

This paper proposes multistream CNN, a novel neural network architecture for robust
acoustic modeling in speech recognition tasks. The proposed architecture processes input …