What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Statistics
- Machine learning
His scientific interests lie mostly in Speech recognition, Artificial intelligence, Music information retrieval, World Wide Web and Multimedia.
His studies in Speech recognition integrate themes in fields like Timbre, Set, Statistical classification, Polyphony and Feature selection.
His Artificial intelligence research integrates issues from Natural language processing, Percussion and Pattern recognition.
His study in Music information retrieval is interdisciplinary in nature, drawing from both Visualization, Information retrieval and Identification.
In general World Wide Web study, his work on Recommender system often relates to the realm of CONTEST, thereby connecting several areas of interest.
Perfecto Herrera works mostly in the field of Context, limiting it down to topics relating to RSS and, in certain cases, Musical, as a part of the same area of interest.
His most cited work include:
- Chroma Binary Similarity and Local Alignment Applied to Cover Song Identification (215 citations)
- Essentia: An Audio Analysis Library for Music Information Retrieval. (202 citations)
- A new approach to evaluating novel recommendations (151 citations)
What are the main themes of his work throughout his whole career to date?
Perfecto Herrera mostly deals with Artificial intelligence, Speech recognition, Natural language processing, Information retrieval and Music information retrieval.
His Artificial intelligence research is multidisciplinary, incorporating perspectives in Machine learning, Musical and Pattern recognition.
Visualization is closely connected to Multimedia in his research, which is encompassed under the umbrella topic of Musical.
Perfecto Herrera applies his multidisciplinary studies on Speech recognition and Audio signal processing in his research.
His Information retrieval research focuses on subjects like Metadata, which are linked to Popular music.
His Music information retrieval research incorporates elements of Statistical classification and Key.
He most often published in these fields:
- Artificial intelligence (40.00%)
- Speech recognition (39.39%)
- Natural language processing (20.61%)
What were the highlights of his more recent work (between 2013-2021)?
- Artificial intelligence (40.00%)
- Rhythm (8.48%)
- Speech recognition (39.39%)
In recent papers he was focusing on the following fields of study:
His primary areas of study are Artificial intelligence, Rhythm, Speech recognition, Electronic dance music and Multimedia.
His research in Artificial intelligence intersects with topics in Natural language processing, Field and Pattern recognition.
His work on Similarity and Pattern recognition as part of general Pattern recognition research is often related to Drum, thus linking different fields of science.
The concepts of his Rhythm study are interwoven with issues in Evolutionary biology, Beat, Perception and Variation.
His Speech recognition study integrates concerns from other disciplines, such as Selection, Decoding methods and Sound.
His Multimedia study combines topics in areas such as Music information retrieval, Musical, Open source and World Wide Web.
Between 2013 and 2021, his most popular works were:
- Two Data Sets for Tempo Estimation and Key Detection in Electronic Dance Music Annotated from User Corrections (18 citations)
- Cross-collection evaluation for music classification tasks (12 citations)
- Key Estimation in Electronic Dance Music (11 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Statistics
- Machine learning
His primary areas of study are Music information retrieval, Multimedia, Audio analyzer, Key and Electronic dance music.
His Multimedia study combines topics from a wide range of disciplines, such as Open source and World Wide Web.
The various areas that Perfecto Herrera examines in his Key study include Tonality, Human–computer interaction, Variety, Electronic music and Operations research.
His Electronic dance music study spans across into fields like Music theory and Umbrella term.
He regularly links together related areas like Speech recognition in his Computation studies.
Perfecto Herrera connects Speech recognition with Recurrence quantification analysis in his research.
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