Science Explorer Back to mapMap
Discussion
Researcher · Vicomtech · Spain

Haritz Arzelus

Haritz Arzelus publishes mostly in Artificial Intelligence, Signal Processing and Language and Linguistics, on topics such as Speech Recognition and Synthesis, Natural Language Processing Techniques and Music and Audio Processing.

ORCID 0000-0002-0731-1317 OpenAlex
World rank
#3,204,948
of 7,710,434 ranked researchers
Rank in Spain
#71,797
of 204,306
Works
32
Citations
152
Citations per work
4.8
h-index
8
i10-index 7Top 56% in Artificial Intelligence
Haritz Arzelus

What does Haritz Arzelus research?

Haritz Arzelus's work is mostly in Computer Science (78%), Arts and Humanities (14%), Psychology (3%).

Physical Sciences: 25 works · 78.0% of their workComputer Science: 25 works · 78.0% of their workArtificial Intelligence: 15 works · 46.8% of their workSignal Processing: 7 works · 22.1% of their workComputer Vision and Pattern Recognition: 2 works · 6.5% of their workInformation Systems: 1 works · 2.6% of their workSocial Sciences: 5 works · 16.9% of their workArts and Humanities: 5 works · 14.3% of their workLanguage and Linguistics: 5 works · 14.3% of their workPsychology: 1 works · 2.6% of their workExperimental and Cognitive Psychology: 1 works · 2.6% of their workEverything else: 2 works · 5.1% of their workTHEIR WORKHaritz Arzelus32works
Physical Sciences78%Social Sciences17%

Their six largest subfields, inside their fields and domains; the grey slice is everything else they publish. The interactive view splits every one of their works down to single topics.

The fields and subfields, with their numbers
    1. Computer Science2578.0%
    1. Arts and Humanities514.3%
    2. Psychology12.6%
  3. Everything else25.1%
  1. 1Artificial Intelligence47% of their works
  2. 2Signal Processing22% of their works
  3. 3Language and Linguistics14% of their works
  4. 4Computer Vision and Pattern Recognition6% of their works
  5. 5Experimental and Cognitive Psychology3% of their works
  6. 6Information Systems3% of their works

Research topics

Which keywords describe Haritz Arzelus's research?

The keywords of their largest research topics: Convolutional Neural Networks, Acoustic Modeling, Deep Neural Networks, Deep Learning, Corpus Linguistics, Neural Machine Translation, Statistical Machine Translation and Audio Signal Classification.

Size is their works in the topics tagged with each word, from their 8 largest topics. Each links to the topic it comes from most.

All 21 words, with their numbers
  1. Convolutional Neural Networks262 topics
  2. Acoustic Modeling171 topic
  3. Deep Neural Networks171 topic
  4. Deep Learning162 topics
  5. Corpus Linguistics152 topics
  6. Neural Machine Translation111 topic
  7. Statistical Machine Translation111 topic
  8. Audio Signal Classification91 topic
  9. Music Information Retrieval91 topic
  10. Neural Networks92 topics
  11. Audio-Visual Speech Recognition71 topic
  12. Language Learning71 topic
  13. Speech Enhancement71 topic
  14. Subtitling71 topic
  15. Machine Translation62 topics
  16. Markov Decision Processes51 topic
  17. Spoken Dialogue Systems51 topic
  18. Translation41 topic
  19. Translator Competence41 topic
  20. Text Classification21 topic
  21. Word Representation21 topic

Where does Haritz Arzelus work?

Haritz Arzelus's main affiliation in the publication record is Vicomtech, Spain.

How many publications and citations does Haritz Arzelus have?

OpenAlex counts 32 works and 152 citations for Haritz Arzelus, an h-index of 8, ranking #3,204,948 of 7,710,434 researchers worldwide on the quality score.

Ranked on field-normalised excellence (50%), output (30%) and citations (20%). Counts come from OpenAlex author records, which occasionally merge different people who share a name or split one person into several.

Papers, co-authors, who cited this work and researchers on the nearest topics have tabs of their own, above. Is this your page? Claim it with your ORCID iD, or request a correction or removal.

Discussion

Ask a question or share a note about Haritz Arzelus. Posts are plain text and can be reported.