Emotion recognition in speech, driven by advances in neural network methodologies, has emerged as a pivotal domain in human–machine interaction.

Today, powered by the latest technologies like Artificial Intelligence (AI), Machine Learning (ML), and Deep Learning, speech recognition is touching new milestones.

Affectiva, the global leader in Artificial Emotional Intelligence, today announced its new cloud-based API for measuring emotion in recorded speech.

Researchers explore a human speech recognition model based on machine learning and deep neural networks. They calculated how many words per sentence a listener understands using automatic speech ...

Microsoft adds emotion recognition to its collection of machine learning APIs, potentially leading to computers that can sense a user's mood by looking at them.

The model allowed the researchers to predict the human speech recognition performance of hearing-impaired listeners with different degrees of hearing loss for a variety of noise maskers with ...

Machine-learning system tackles speech and object recognition, all at once Model learns to pick out objects within an image, using spoken descriptions Date: September 18, 2018 Source ...

Machine learning is becoming increasingly powerful, with a number of researchers and startups developing solutions that can analyze our speech for various things, including neurological dissorders.

Facial recognition has come a long way using machine learning, but identifying a person’s emotional state based purely on looking at a person’s face is missing key information.