Recently, audio segmentation has attracted research interest because of its usefulness in several applications like audio indexing and retrieval, subtitling, monitoring of acoustic scenes, etc. Moreover, a previous audio segmentation stage may be useful to improve the robustness of speech technologies like automatic speech recognition and speaker diarization. In this article, we present the eva...

The vocal training is useful for beginners to learn how to correctly sing, and for professional singers to tune their voice and expand their frequency range. In the paper, we propose a study on vocal training by analyzing voice pitch on android platform. Vocal training requires a vocal coach who is always besides you to correct your mistakes. However, beginner who wants to learn singing for fun...

Successful face detection and facial feature extraction is crucial for for a variety of applications, including speech recognition and fatigue monitoring. Detecting and tracking faces in a moving automobile is challenging because of a variety of reasons. Among these reasons are changing poses, extreme lighting changes and shadowing. In this paper, we investigate two approaches for shadow compen...

Feature extraction is a crucial step in developing any speech and language processing applications. Extracting features from speech can be viewed in two major perspectives, in the initial perspective a feature to represent speech signal is extracted by treating speech signal as any non-stationary signal. The later perspective is by considering speech as a special signal that has its own product...

Performance of an automatic speech recognition system drops dramatically in the presence of background noise unlike the human auditory system which is more adept at noisy speech recognition. This paper proposes a novel auditory modeling algorithm which is integrated into the feature extraction front-end for Hidden Markov Model (HMM). The proposed algorithm is named LTFC which simulates properti...

A number of researches on Automatic Speech Recognition (ASR) have been carried out using a recognition model based on feature extraction and classification. With such an approach, the same set of features are extracted at fixed time intervals (typically every 10 msecs.) and classification is based on distances between feature patterns and prototypes &EVINSON 81) or likelihoods computed from a M...

Annotations of speech recordings are a fundamental part of any unit selection speech synthesiser. However, obtaining flawless annotations is an almost impossible task. Manual techniques can achieve the most accurate annotations, provided that enough time is available to analyse every phone individually. Automatic annotation techniques are a lot faster than manual, doing the task in a much more ...

In this paper, we investigate the recognition of speech produced by a person with an articulation disorder resulting from athetoid cerebral palsy. The articulation of the first spoken words tends to become unstable due to strain on speech muscles, and that causes degradation of speech recognition. Therefore, we propose a robust feature extraction method using a convolutive bottleneck network (C...

The need for an automatic lip-reading system is ever increasing. Infact, today, extraction and reliable analysis of facial movements make up an important part in many multimedia systems such as videoconference, low communication systems, lip-reading systems. In addition, visual information is imperative among people with special needs. We can imagine, for example, a dependent person ordering a ...