What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Machine learning
- Speech recognition
His main research concerns Artificial intelligence, Speech recognition, Facial expression, Cognitive psychology and Affective computing.
His research integrates issues of Machine learning and Natural language processing in his study of Artificial intelligence.
His Speech recognition study combines topics in areas such as Sadness, Anger and Computer vision.
His work deals with themes such as Motion capture and Happiness, which intersect with Anger.
His work in Facial expression addresses issues such as Gesture, which are connected to fields such as Facial recognition system and Human communication.
His Affective computing research includes elements of Sentence, Coarticulation and Affective science.
His most cited work include:
- IEMOCAP: interactive emotional dyadic motion capture database (895 citations)
- Analysis of emotion recognition using facial expressions, speech and multimodal information (617 citations)
- The Geneva Minimalistic Acoustic Parameter Set (GeMAPS) for Voice Research and Affective Computing (528 citations)
What are the main themes of his work throughout his whole career to date?
His scientific interests lie mostly in Artificial intelligence, Speech recognition, Computer vision, Emotion recognition and Natural language processing.
The concepts of his Artificial intelligence study are interwoven with issues in Machine learning and Pattern recognition.
His studies deal with areas such as Feature extraction and Feature as well as Speech recognition.
His Computer vision research incorporates themes from Head and Distraction.
His studies in Natural language processing integrate themes in fields like Affective computing, Classifier and Emotion perception.
His research in Facial expression intersects with topics in Sadness and Anger.
He most often published in these fields:
- Artificial intelligence (55.29%)
- Speech recognition (46.47%)
- Computer vision (15.29%)
What were the highlights of his more recent work (between 2019-2021)?
- Artificial intelligence (55.29%)
- Discriminative model (5.88%)
- Speech recognition (46.47%)
In recent papers he was focusing on the following fields of study:
Carlos Busso mainly investigates Artificial intelligence, Discriminative model, Speech recognition, Feature and Task analysis.
Carlos Busso combines subjects such as Machine learning and Computer vision with his study of Artificial intelligence.
His research in Speech recognition is mostly concerned with Emotion recognition.
His Feature research is multidisciplinary, incorporating perspectives in Externalization, Natural and Database.
Carlos Busso interconnects Multi-task learning, Ordinal data and Speech processing in the investigation of issues within Task analysis.
His Manner of articulation research is multidisciplinary, relying on both Sadness, Anger, Facial expression and Happiness.
Between 2019 and 2021, his most popular works were:
- The Ordinal Nature of Emotions: An Emerging Approach (29 citations)
- Semi-Supervised Speech Emotion Recognition With Ladder Networks (11 citations)
- End-to-End Audiovisual Speech Recognition System With Multitask Learning (8 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Machine learning
- Speech recognition
Carlos Busso focuses on Task analysis, Cognitive psychology, Multi-task learning, Speech processing and Artificial intelligence.
Carlos Busso has researched Task analysis in several fields, including Value, Affective computing, Representation and Ordinal data.
Carlos Busso has included themes like Context and Loneliness in his Cognitive psychology study.
His biological study spans a wide range of topics, including Machine learning, Feature and Robustness.
His Robustness study combines topics from a wide range of disciplines, such as Feature extraction and Discriminative model.
His Speech processing research is within the category of Speech recognition.
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