Óscar Saz

43 papers receiving 373 citations

Peers

Óscar Saz
Comparison fields: 5 of 50
  • Artificial Intelligence 312
  • Signal Processing 164
  • Experimental and Cognitive Psychology 78
  • Physiology 49
  • Developmental and Educational Psychology 43
Replace Sheri Hunnicutt with:
Sheri Hunnicutt Sweden
Carlos Vaquero Spain
Febe de Wet South Africa
Graham Neubig Japan
Taniya Mishra United States
Éva Székely Sweden
Julie Carson-Berndsen Ireland
Judith M. Kessens Netherlands
Pirros Tsiakoulis Greece
João P. Cabral Ireland
Óscar Saz relative to Sheri Hunnicutt Sweden Sheri Hunnicutt's profile →
Citations per field
00.5×10×13.3×
Sheri Hunnicutt · 1×
Citations per year

Countries citing papers authored by Óscar Saz

Since Specialization
Citations

This map shows the geographic impact of Óscar Saz's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Óscar Saz with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Óscar Saz more than expected).

Fields of papers citing papers by Óscar Saz

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Óscar Saz. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Óscar Saz. The network helps show where Óscar Saz may publish in the future.

Co-authorship network of co-authors of Óscar Saz

This figure shows the co-authorship network connecting the top 25 collaborators of Óscar Saz. A scholar is included among the top collaborators of Óscar Saz based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Óscar Saz. Óscar Saz is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
#WorkIndexed citations
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Unsupervised Domain Discovery Using Latent Dirichlet Allocation for Acoustic Modelling in Speech Recognition
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Data-Selective Transfer Learning for Multi-Domain Speech Recognition
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6 8
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The USFD SLT System for IWSLT 2014
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8
Automatic Transcription of Multi-Genre Media Archives
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9 3
10 2
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The Alborada-I3A Corpus of Disordered Speech
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12 1
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14 77
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A novel corpus of children 2 s disordered speech.
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17 16
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COMUNICA - tools for speech and language therapy.
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19 6
20 2

About Óscar Saz

Óscar Saz is a scholar working on Signal Processing, Artificial Intelligence and Experimental and Cognitive Psychology, having authored 43 papers that have together received 410 indexed citations. Recurring topics across this work include Speech Recognition and Synthesis (35 papers), Speech and Audio Processing (16 papers) and Speech and dialogue systems (14 papers). The work is most often cited by research in Signal Processing (164 citations), Artificial Intelligence (312 citations) and Occupational Therapy (28 citations). Óscar Saz has collaborated with scholars based in Spain, United Kingdom and United States. Frequent co-authors include Eduardo Lleida, Thomas Hain, Carlos Vaquero, Richard C. Rose, Madina Hasan, Philip C. Woodland, Mark Gales, Pierre Lanchantin, Antonio Miguel and Peter Bell. Their work appears in journals such as IEEE Transactions on Audio Speech and Language Processing, Speech Communication and Multimedia Tools and Applications.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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