2011Unpublished venueRequires access

Smart recognition and synthesis of emotional speech for embedded systems with natural user interfaces

Mario Malcangi

Open publisher page 4 citations

Abstract

The importance of the emotion information in human speech has been growing in recent years due to increasing use of natural user interfacing in embedded systems. Speech-based human-machine communication has the advantage of a high degree of usability, but it need not be limited to speech-to-text and text-to-speech capabilities. Emotion recognition in uttered speech has been considered in this research to integrate a speech recognizer/synthesizer with the capacity to recognize and synthesize emotion. This paper describes a complete framework for recognizing and synthesizing emotional speech based on smart logic (fuzzy logic and artificial neural networks). Time-domain signal-processing algorithms has been applied to reduce computational complexity at the feature-extraction level. A fuzzy-logic engine was modeled to make inferences about the emotional content of the uttered speech. An artificial neural network was modeled to synthesize emotive speech. Both were designed to be integrated into an embedded handheld device that implements a speech-based natural user interface (NUI).

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What this paper is about

The importance of the emotion information in human speech has been growing in recent years due to increasing use of natural user interfacing in embedded systems. Speech-based human-machine communication has the advantage of a high degree of usability, but it need not be limited to speech-to-text and text-to-speech capabilities. Emotion recognition in uttered speech has been considered in this research to integrate a speech recognizer/synthesizer with the capacity to recognize and synthesize emotion. This paper describes a complete framework for recognizing and synthesizing emotional speech based on smart logic (fuzzy logic and artificial neural networks). Time-domain signal-processing algorithms has been applied to reduce computational complexity at the feature-extraction level. A fuzzy-logic engine was modeled to make inferences about the emotional content of the uttered speech. An artificial neural network was modeled to synthesize emotive speech. Both were designed to be integrated into an embedded handheld device that implements a speech-based natural user interface (NUI).

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OpenAlex reports 4 citations for this work. Citation counts describe recorded attention and do not establish research quality.

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Available abstract

The importance of the emotion information in human speech has been growing in recent years due to increasing use of natural user interfacing in embedded systems. Speech-based human-machine communication has the advantage of a high degree of usability, but it need not be limited to speech-to-text and text-to-speech capabilities. Emotion recognition in uttered speech has been considered in this research to integrate a speech recognizer/synthesizer with the capacity to recognize and synthesize emotion. This paper describes a complete framework for recognizing and synthesizing emotional speech based on smart logic (fuzzy logic and artificial neural networks). Time-domain signal-processing algorithms has been applied to reduce computational complexity at the feature-extraction level. A fuzzy-logic engine was modeled to make inferences about the emotional content of the uttered speech. An artificial neural network was modeled to synthesize emotive speech. Both were designed to be integrated into an embedded handheld device that implements a speech-based natural user interface (NUI).

Key concepts: Computer science, Speech synthesis, Speech analytics, Speech recognition, Emotive, Artificial neural network, Natural user interface, Voice activity detection

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