Swapna Agarwalla

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Speech is a rich source of information. The speech samples can not only retain what is being spoken but also the emotional state of the speaker. In this paper, the dynamics of the prosodic features and the spectral features have been used to encode the mood content of speakers of Assamese language with dialectal components. A composite feature set has been(More)
Mood content in spoken word recognition is an important element in formulation of a decision support system (DSS). Many times it becomes integral components of human computer interaction (HCI) systems based on speech recognition with language orientation. In this paper, we propose a mood verification system of speakers of Assamese language with dialectal(More)
Automatic Speaker Recognition (ASR) and related issues are continuously evolving as inseparable elements of Human Computer Interaction (HCI). With assimilation of emerging concepts like big data and Internet of Things (IoT) as extended elements of HCI, ASR techniques are found to be passing through a paradigm shift. Oflate, learning based techniques have(More)
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