David Escudero-Mancebo

1.6k total citations · 1 hit paper
69 papers, 969 citations indexed

About

David Escudero-Mancebo is a scholar working on Artificial Intelligence, Experimental and Cognitive Psychology and Language and Linguistics. According to data from OpenAlex, David Escudero-Mancebo has authored 69 papers receiving a total of 969 indexed citations (citations by other indexed papers that have themselves been cited), including 43 papers in Artificial Intelligence, 35 papers in Experimental and Cognitive Psychology and 9 papers in Language and Linguistics. Recurrent topics in David Escudero-Mancebo's work include Phonetics and Phonology Research (34 papers), Speech Recognition and Synthesis (30 papers) and Speech and dialogue systems (29 papers). David Escudero-Mancebo is often cited by papers focused on Phonetics and Phonology Research (34 papers), Speech Recognition and Synthesis (30 papers) and Speech and dialogue systems (29 papers). David Escudero-Mancebo collaborates with scholars based in Spain, Netherlands and France. David Escudero-Mancebo's co-authors include Valentín Cardeñoso-Payo, Carlos Vivaracho‐Pascual, César González-Ferreras, Inma Hernáez, Juan J. Igarza, Marcos Faúndez-Zanuy, Javier Ortega-García, Julián Fiérrez, J. M. Gonzalez and Antonio Bonafonte and has published in prestigious journals such as IEEE Access, Applied Sciences and IEEE Transactions on Audio Speech and Language Processing.

In The Last Decade

David Escudero-Mancebo

65 papers receiving 886 citations

Hit Papers

MCYT baseline corpus: a bimodal biometric database 2003 2026 2010 2018 2003 100 200 300 400

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
David Escudero-Mancebo Spain 14 486 426 293 241 173 69 969
Sarmad Hussain Pakistan 18 564 1.2× 273 0.6× 123 0.4× 76 0.3× 60 0.3× 68 805
Fadi Biadsy United States 20 821 1.7× 158 0.4× 295 1.0× 160 0.7× 57 0.3× 41 1.0k
Judy Hochberg United States 12 234 0.5× 291 0.7× 129 0.4× 145 0.6× 28 0.2× 14 698
M. Ortega United States 8 253 0.5× 1.3k 3.1× 169 0.6× 40 0.2× 44 0.3× 12 1.5k
Roberto Pieraccini United States 25 1.8k 3.8× 326 0.8× 402 1.4× 209 0.9× 78 0.5× 91 2.1k
Gérard Chollet France 17 669 1.4× 287 0.7× 773 2.6× 104 0.4× 73 0.4× 143 1.1k
Mohammed Hasanuzzaman Ireland 16 355 0.7× 202 0.5× 40 0.1× 81 0.3× 77 0.4× 64 751
Luis Villaseñor-Pineda Mexico 20 691 1.4× 336 0.8× 233 0.8× 145 0.6× 216 1.2× 93 1.3k
Javier Ferreiros Spain 15 461 0.9× 129 0.3× 164 0.6× 66 0.3× 18 0.1× 88 722
Oya Çeliktutan United Kingdom 15 206 0.4× 467 1.1× 92 0.3× 203 0.8× 28 0.2× 56 853

Countries citing papers authored by David Escudero-Mancebo

Since Specialization
Citations

This map shows the geographic impact of David Escudero-Mancebo'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 David Escudero-Mancebo with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites David Escudero-Mancebo more than expected).

Fields of papers citing papers by David Escudero-Mancebo

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by David Escudero-Mancebo. 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 David Escudero-Mancebo. The network helps show where David Escudero-Mancebo may publish in the future.

Co-authorship network of co-authors of David Escudero-Mancebo

This figure shows the co-authorship network connecting the top 25 collaborators of David Escudero-Mancebo. A scholar is included among the top collaborators of David Escudero-Mancebo 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 David Escudero-Mancebo. David Escudero-Mancebo 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
1.
González-Ferreras, César, et al.. (2023). Prosodic Feature Analysis for Automatic Speech Assessment and Individual Report Generation in People with Down Syndrome. Applied Sciences. 14(1). 293–293. 1 indexed citations
2.
Escudero-Mancebo, David, et al.. (2021). Evaluating the Impact of an Autonomous Playing Mode in a Learning Game to Train Oral Skills of Users With Down Syndrome. IEEE Access. 9. 93480–93496. 3 indexed citations
3.
Cardeñoso-Payo, Valentín, et al.. (2021). Automatic Speech Recognition (ASR) Systems Applied to Pronunciation Assessment of L2 Spanish for Japanese Speakers. Applied Sciences. 11(15). 6695–6695. 8 indexed citations
4.
Escudero-Mancebo, David, et al.. (2020). Using Challenges to Enhance a Learning Game for Pronunciation Training of English as a Second Language. IEEE Access. 8. 74250–74266. 21 indexed citations
5.
Escudero-Mancebo, David, et al.. (2020). Assessing Pronunciation Improvement in Students of English Using a Controlled Computer-Assisted Pronunciation Tool. IEEE Transactions on Learning Technologies. 13(2). 269–282. 30 indexed citations
6.
7.
Martínez‐Castilla, Pastora, et al.. (2019). Automatic Assessment of Prosodic Quality in Down Syndrome: Analysis of the Impact of Speaker Heterogeneity. Applied Sciences. 9(7). 1440–1440. 15 indexed citations
8.
Escudero-Mancebo, David, et al.. (2016). Measuring Pronunciation Improvement in Users of CAPT Tool TipTopTalk. Conference of the International Speech Communication Association. 1178–1179. 4 indexed citations
9.
Escudero-Mancebo, David, et al.. (2015). Implementation and test of a serious game based on minimal pairs for pronunciation training. UVaDOC UVaDOC University of Valladolid Documentary Repository (University of Valladolid). 125–130. 7 indexed citations
10.
González-Ferreras, César, et al.. (2014). Assessment of Non-native Prosody for Spanish as L2 using quantitative scores and perceptual evaluation. Language Resources and Evaluation. 3967–3972. 2 indexed citations
11.
Escudero-Mancebo, David, et al.. (2014). On the use of a fuzzy classifier to speed up the Sp ToBI labeling of the Glissando Spanish corpus. Language Resources and Evaluation. 1962–1969. 1 indexed citations
13.
Escudero-Mancebo, David, et al.. (2010). Procedure for assessing the reliability of prosodic judgements using sp-TOBI labeling system. paper 922–0. 1 indexed citations
14.
Escudero-Mancebo, David, et al.. (2009). On the definition of a prosodically balaced corpus: combining greedy algorithms with expert guided manipulation. Procesamiento del lenguaje natural. 93–101. 3 indexed citations
15.
Escudero-Mancebo, David, et al.. (2009). Hacia la definición de un corpus equilibrado prosódicamente: estrategia combinada de algoritmos voraces y manipulación de expertos. Procesamiento del lenguaje natural. 43. 93–101.
16.
Segura, Jordi Adell, Antonio Bonafonte, & David Escudero-Mancebo. (2007). Statistical analysis of filled pauses 2 rhythm for disfluent speech synthesis.. SSW. 223–227. 2 indexed citations
17.
Segura, Jordi Adell, Antonio Bonafonte, & David Escudero-Mancebo. (2006). Disfluent speech analysis and synthesis: a preliminary approach. paper 152–0. 13 indexed citations
18.
Segura, Jordi Adell, Antonio Bonafonte, & David Escudero-Mancebo. (2005). Analysis of prosodic features : towards modelling of emotional and pragmatic attributes of speech. Procesamiento del lenguaje natural. 35(35). 277–283. 20 indexed citations
19.
Escudero-Mancebo, David. (2003). Modelado estadístico de entonación con funciones de Bézier: aplicaciones a la conversión texto-voz en español. Procesamiento del lenguaje natural. 30(30). 125–126. 8 indexed citations
20.
Escudero-Mancebo, David & Valentín Cardeñoso-Payo. (2001). Modelo cuantitativo de entonación del español.. Procesamiento del lenguaje natural. 27(27). 233–240. 1 indexed citations

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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