Berrak Şişman

2.1k total citations · 1 hit paper
59 papers, 1.2k citations indexed

About

Berrak Şişman is a scholar working on Artificial Intelligence, Signal Processing and Experimental and Cognitive Psychology. According to data from OpenAlex, Berrak Şişman has authored 59 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 53 papers in Artificial Intelligence, 37 papers in Signal Processing and 12 papers in Experimental and Cognitive Psychology. Recurrent topics in Berrak Şişman's work include Speech Recognition and Synthesis (49 papers), Speech and Audio Processing (36 papers) and Music and Audio Processing (20 papers). Berrak Şişman is often cited by papers focused on Speech Recognition and Synthesis (49 papers), Speech and Audio Processing (36 papers) and Music and Audio Processing (20 papers). Berrak Şişman collaborates with scholars based in Singapore, China and United States. Berrak Şişman's co-authors include Haizhou Li, Kun Zhou, Junichi Yamagishi, Simon King, Rui Liu, Guanglai Gao, Mingyang Zhang, Rui Liu, Kay Chen Tan and Björn W. Schuller and has published in prestigious journals such as Neural Networks, IEEE Signal Processing Letters and Speech Communication.

In The Last Decade

Berrak Şişman

51 papers receiving 1.1k citations

Hit Papers

An Overview of Voice Conversion and Its Challenges: From ... 2020 2026 2022 2024 2020 50 100 150 200
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. An Overview of Voice Conversion and Its Challenges: From Statistical Modeling to Deep Learning
    2020 224 citations Berrak Şişman, Haizhou Li et al. profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Berrak Şişman Singapore 19 926 726 150 150 65 59 1.2k
Denis Jouvet France 13 775 0.8× 627 0.9× 111 0.7× 157 1.0× 30 0.5× 87 940
Mitchell McLaren United States 24 1.7k 1.8× 1.6k 2.2× 184 1.2× 94 0.6× 30 0.5× 84 1.9k
Longbiao Wang China 16 603 0.7× 623 0.9× 89 0.6× 139 0.9× 50 0.8× 62 771
Pegah Ghahremani United States 12 1.1k 1.2× 901 1.2× 65 0.4× 136 0.9× 42 0.6× 18 1.3k
Anil Kumar Vuppala India 17 671 0.7× 636 0.9× 90 0.6× 194 1.3× 90 1.4× 88 831
Michael W. Macon United States 12 713 0.8× 637 0.9× 139 0.9× 132 0.9× 50 0.8× 24 858
Takashi Nose Japan 14 962 1.0× 697 1.0× 93 0.6× 222 1.5× 20 0.3× 116 1.1k
Eva Navas Spain 16 692 0.7× 716 1.0× 116 0.8× 356 2.4× 74 1.1× 87 958
Sachin Kajarekar United States 20 1.3k 1.4× 1.2k 1.6× 119 0.8× 84 0.6× 19 0.3× 52 1.4k
Kushal Lakhotia Israel 10 830 0.9× 456 0.6× 94 0.6× 93 0.6× 30 0.5× 11 950

Countries citing papers authored by Berrak Şişman

Since Specialization
Citations

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

Fields of papers citing papers by Berrak Şişman

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Berrak Şişman

This figure shows the co-authorship network connecting the top 25 collaborators of Berrak Şişman. A scholar is included among the top collaborators of Berrak Şişman 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 Berrak Şişman. Berrak Şişman 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
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Chen, Nancy F., et al.. (2025). PRESENT: Zero-Shot Text-to-Prosody Control. IEEE Signal Processing Letters. 32. 776–780.
3.
Şişman, Berrak, et al.. (2024). Enhanced Facial Landmarks Detection for Patients with Repaired Cleft Lip and Palate. 1–10. 2 indexed citations
4.
Zhou, Kun, et al.. (2024). Mixed-EVC: Mixed Emotion Synthesis and Control in Voice Conversion. 180–186. 1 indexed citations
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Moro-Velázquez, Laureano, et al.. (2024). Odyssey 2024 - Speech Emotion Recognition Challenge: Dataset, Baseline Framework, and Results. 247–254. 9 indexed citations
7.
Melechovský, Jan, Ambuj Mehrish, Berrak Şişman, & Dorien Herremans. (2024). Accent Conversion in Text-to-Speech Using Multi-Level VAE and Adversarial Training. ARCA (Università Ca' Foscari Venezia). 473–476. 1 indexed citations
8.
Şişman, Berrak, et al.. (2024). Exploring speech style spaces with language models: Emotional TTS without emotion labels. 194–200. 1 indexed citations
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Lin, Wei-Cheng, et al.. (2024). Versatile Audio-Visual Learning for Emotion Recognition. IEEE Transactions on Affective Computing. 16(1). 306–318. 8 indexed citations
13.
Liu, Rui, et al.. (2021). FastTalker: A neural text-to-speech architecture with shallow and group autoregression. Neural Networks. 141. 306–314. 8 indexed citations
14.
Zhou, Kun, Berrak Şişman, Rui Liu, & Haizhou Li. (2021). Seen and Unseen Emotional Style Transfer for Voice Conversion with A New Emotional Speech Dataset. 920–924. 108 indexed citations
15.
Zhou, Kun, Berrak Şişman, Rui Liu, & Haizhou Li. (2021). Emotional voice conversion: Theory, databases and ESD. Speech Communication. 137. 1–18. 80 indexed citations
16.
Zhou, Kun, et al.. (2020). Converting Anyone’s Emotion: Towards Speaker-Independent Emotional Voice Conversion. 3416–3420. 35 indexed citations
17.
Zhou, Kun, et al.. (2020). VAW-GAN for Singing Voice Conversion with Non-parallel Training Data. Asia-Pacific Signal and Information Processing Association Annual Summit and Conference. 514–519. 1 indexed citations
18.
Zhou, Kun, Berrak Şişman, & Haizhou Li. (2020). Transforming Spectrum and Prosody for Emotional Voice Conversion with Non-Parallel Training Data. 49 indexed citations
19.
Wang, Zhichao, Yi Zhou, Mingyang Zhang, et al.. (2020). The NUS & NWPU system for Voice Conversion Challenge 2020. 170–174. 3 indexed citations
20.
Gao, Xiaoxue, et al.. (2018). NUS-HLT Spoken Lyrics and Singing (SLS) Corpus. 110. 1–6. 4 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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