نتایج جستجو برای: speech recognition
تعداد نتایج: 337006 فیلتر نتایج به سال:
speech emotion recognition (ser) is a new and challenging research area with a wide range of applications in man-machine interactions. the aim of a ser system is to recognize human emotion by analyzing the acoustics of speech sound. in this study, we propose spectral pattern features (sps) and harmonic energy features (hes) for emotion recognition. these features extracted from the spectrogram ...
For many years, speech has been the most natural and efficient means of information exchange for human beings. With the advancement of technology and the prevalence of computer usage, the design and production of speech recognition systems have been considered by researchers. Among this, lip-reading techniques encountered with many challenges for speech recognition, that one of the challenges b...
The performance of automatic speech recognition (ASR) systems is adversely affected by the variations in speakers, audio channels and environmental conditions. Making these systems robust to these variations is still a big challenge. One of the main sources of variations in the speakers is the differences between their Vocal Tract Length (VTL). Vocal Tract Length Normalization (VTLN) is an effe...
Speech Emotion Recognition, abbreviated as SER, is the act of attempting to recognize human emotion and affective states from speech. This capitalizing on fact that voice often reflects underlying through tone pitch. also phenomenon animals like dogs horses employ be able understand emotion. SER tough because emotions are subjective annotating audio challenging.The main objective this recognizi...
Speech Emotion Recognition (SER) is a new and challenging research area with a wide range of applications in man-machine interactions. The aim of a SER system is to recognize human emotion by analyzing the acoustics of speech sound. In this study, we propose Spectral Pattern features (SPs) and Harmonic Energy features (HEs) for emotion recognition. These features extracted from the spectrogram ...
Background: Many elderly individuals complain of difficulty in understanding speech in noise despite having normal hearing thresholds. According to previous studies, auditory training leads to improvement in speech-in-noise perception, but these studies did not consider the etiology, so their results cannot be generalized. The present study aimed at investigating the effectiveness of envelope-b...
Background and Aim: The applicability of any technology to enter a certain field is determined by defining the advantages and disadvantages of the system in that field. The aim of this study is to show the advantages and limitations of using speech recognition systems in health care and providing practical solutions to improve the acceptability of the system in that field. Materials and M...
A variety of methods are used for speaker adaptation in speech recognition. In some techniques, such as MAP estimation, only the models with available training data are updated. Hence, large amounts of training data are required in order to have significant recognition improvements. In some others, such as MLLR, where several general transformations are applied to model clusters, the results ar...
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