نتایج جستجو برای: speech recognition
تعداد نتایج: 337006 فیلتر نتایج به سال:
Speech recognition is a subfield of artificial intelligence that develops technologies to convert speech utterance into transcription. So far, various methods such as hidden Markov models and artificial neural networks have been used to develop speech recognition systems. In most of these systems, the speech signal frames are processed uniformly, while the information is not evenly distributed ...
Accurate gender classification is useful in speech and speaker recognition as well as speech emotion classification, because a better performance has been reported when separate acoustic models are employed for males and females. Gender classification is also apparent in face recognition, video summarization, human-robot interaction, etc. Although gender classification is rather mature in a...
background and aim: speech understanding almost never occurs in silence. verbal communication often occurs in environments where multiple speakers are talking. in such environments, babbling noise masks speech comprehension. consonants, in comparison to vowels, are more sensitive to noise masking. consonants provide most acoustic information needed for comprehending the meaning of the word. sin...
Background: Variability in speech performance is a major concern for children with cochlear implants (CIs). Spectral resolution is an important acoustic component in speech perception. Considerable variability and limitations of spectral resolution in children with CIs may lead to individual differences in speech performance. The aim of this study was to assess the correlation between auditory ...
Abstract Recent developments in robotics automation have motivated researchers to improve the efficiency of interactive systems by making a natural man-machine interaction. Since speech is the most popular method of communication, recognizing human emotions from speech signal becomes a challenging research topic known as Speech Emotion Recognition (SER). In this study, we propose a Persian em...
this paper introduces a novel approach to improve performance of speech recognition systems using a combination of features obtained from speech reconstructed phase space (rps) and frequency domain analysis. by choosing an appropriate value for the dimension, reconstructed phase space is assured to be topologically equivalent to the dynamics of the speech production system, and could therefore ...
In order to facilitate the entry of data into the computer and its digitalization, automatic recognition of printed texts and manuscripts is one of the considerable aid to many applications. Research on automatic document recognition started decades ago with the recognition of isolated digits and letters, and today, due to advancements in machine learning methods, efforts are being made to iden...
مطالعات بر روی نحوه ادراک گفتار انسان نشان می دهد که مغز انسان به وقایع خاصی در سیگنال گفتار حساسیت بیشتری نشان می دهد و این نواحی حاوی اطلاعات متمایزکننده مفیدی برای واحدهای صوتی پایه است. ماهیت این وقایع بعنوان واحدهای پایه واقعی حاوی اطلاعات غنی و مهم گفتار، از نظر زبان شناسی و مهندسی در دست بررسی است. از سوی دیگر در بررسی جنبه های زیستی ادراک گفتار توسط مغز انسان دیدگاههایی وجود دارد که ن...
Although, speech recognition systems are widely used and their accuracies are continuously increased, there is a considerable performance gap between their accuracies and human recognition ability. This is partially due to high speaker variations in speech signal. Deep neural networks are among the best tools for acoustic modeling. Recently, using hybrid deep neural network and hidden Markov mo...
Phoneme recognition is one of the fundamental phases of automatic speech recognition. Coarticulation which refers to the integration of sounds, is one of the important obstacles in phoneme recognition. In other words, each phone is influenced and changed by the characteristics of its neighbor phones, and coarticulation is responsible for most of these changes. The idea of modeling the effects o...
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