Miquel Espi

421 total citations
13 papers, 295 citations indexed

About

Miquel Espi is a scholar working on Signal Processing, Artificial Intelligence and Electrical and Electronic Engineering. According to data from OpenAlex, Miquel Espi has authored 13 papers receiving a total of 295 indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Signal Processing, 9 papers in Artificial Intelligence and 2 papers in Electrical and Electronic Engineering. Recurrent topics in Miquel Espi's work include Speech and Audio Processing (12 papers), Music and Audio Processing (10 papers) and Speech Recognition and Synthesis (9 papers). Miquel Espi is often cited by papers focused on Speech and Audio Processing (12 papers), Music and Audio Processing (10 papers) and Speech Recognition and Synthesis (9 papers). Miquel Espi collaborates with scholars based in Japan, United States and Germany. Miquel Espi's co-authors include Masakiyo Fujimoto, Tomohiro Nakatani, Keisuke Kinoshita, Marc Delcroix, Takuya Yoshioka, Shoko Araki, Atsunori Ogawa, Nobutaka Ito, Takuya Higuchi and Chengzhu Yu and has published in prestigious journals such as EURASIP Journal on Advances in Signal Processing, IEICE Transactions on Information and Systems and Scientific Programming.

In The Last Decade

Miquel Espi

13 papers receiving 267 citations

Peers

Miquel Espi
Daiki Takeuchi Japan
Xiang Hao China
Cheng Yu Taiwan
Laurent Mauuary France
Aswin Shanmugam Subramanian United States
Biing-Hwang Juang United States
Sacha Krstulović France
Kouhei Sekiguchi Japan
Daiki Takeuchi Japan
Miquel Espi
Citations per year, relative to Miquel Espi Miquel Espi (= 1×) peers Daiki Takeuchi

Countries citing papers authored by Miquel Espi

Since Specialization
Citations

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

Fields of papers citing papers by Miquel Espi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Miquel Espi. 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 Miquel Espi. The network helps show where Miquel Espi may publish in the future.

Co-authorship network of co-authors of Miquel Espi

This figure shows the co-authorship network connecting the top 25 collaborators of Miquel Espi. A scholar is included among the top collaborators of Miquel Espi 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 Miquel Espi. Miquel Espi is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

13 of 13 papers shown
1.
Araki, Shoko, Masakiyo Fujimoto, Takuya Yoshioka, et al.. (2015). Deep Learning Based Distant-talking Speech Processing in Real-world Sound Environments. NTT technical review. 13(11). 19–24. 2 indexed citations
2.
Delcroix, Marc, Takuya Yoshioka, Atsunori Ogawa, et al.. (2015). Strategies for distant speech recognitionin reverberant environments. EURASIP Journal on Advances in Signal Processing. 2015(1). 37 indexed citations
3.
Espi, Miquel, Masakiyo Fujimoto, Keisuke Kinoshita, & Tomohiro Nakatani. (2015). Feature extraction strategies in deep learning based acoustic event detection. 2922–2926. 3 indexed citations
4.
Yoshioka, Takuya, Nobutaka Ito, Marc Delcroix, et al.. (2015). The NTT CHiME-3 system: Advances in speech enhancement and recognition for mobile multi-microphone devices. 436–443. 166 indexed citations
5.
Espi, Miquel, Masakiyo Fujimoto, Keisuke Kinoshita, & Tomohiro Nakatani. (2015). Exploiting spectro-temporal locality in deep learning based acoustic event detection. EURASIP Journal on Audio Speech and Music Processing. 2015(1). 58 indexed citations
6.
Espi, Miquel, Masakiyo Fujimoto, & Tomohiro Nakatani. (2015). Acoustic Event Detection in Speech Overlapping Scenarios Based on High-Resolution Spectral Input and Deep Learning. IEICE Transactions on Information and Systems. E98.D(10). 1799–1807. 3 indexed citations
7.
8.
Delcroix, Marc, Takuya Yoshioka, Atsunori Ogawa, et al.. (2014). Defeating reverberation: Advanced dereverberation and recognition techniques for hands-free speech recognition. 14. 522–526. 1 indexed citations
9.
Espi, Miquel, Masakiyo Fujimoto, Daisuke Saito, Nobutaka Ono, & Shigeki Sagayama. (2012). A tandem connectionist model using combination of multi-scale spectro-temporal features for acoustic event detection. 4625. 4293–4296. 8 indexed citations
10.
Espi, Miquel, Shigeki Miyabe, Takuya Nishimoto, Nobutaka Ono, & Shigeki Sagayama. (2011). Using spectral fluctuation of speech in multi-feature HMM-based voice activity detection. 2613–2616. 3 indexed citations
11.
Espi, Miquel, Shigeki Miyabe, Takuya Nishimoto, Nobutaka Ono, & Shigeki Sagayama. (2010). Analysis on speech characteristics for robust voice activity detection. 151–156. 2 indexed citations
12.
Espi, Miquel, et al.. (2009). On the mandatory part of frequency spectrum of whispering signal in order to synthesize pseudo-voice (音声). Scientific Programming. 109(10). 17–20. 1 indexed citations
13.
Espi, Miquel, et al.. (2009). On the Mandatory Part of Frequency Spectrum of Whispering Signal in Order to Synthesize Pseudo-Voice. IEICE Technical Report; IEICE Tech. Rep.. 109(10). 17–20. 2 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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2026