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Speech Emotion Recognition through Machine Learning

As emotions play a vital role in communication, the detection and analysis of the same is of vital importance in today’s digital world of remote communication. Emotion detection is a challenging task because emotions are subjective. There is no common consensus on how to measure or categorize them. We define a SER system as a collection of methodologies that process and classify speech signals to detect emotions embedded in them. Such a system can find use in a wide variety of application areas like interactive voice based-assistant or caller-agent conversation analysis. The study attempts to detect underlying emotions in recorded speech by analysing the acoustic features of the audio data of recordings.

Know More : Speech Recognition(SER) through Machine Learning

New SaaS-based solutions enable enterprise customers to accelerate digital transformation EDISON, N.J. — October 5, 2021 — Brillio, a global […]

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