2026 Rohit Prabhavalkar: Computer Science Researcher – H-Index, Publications & Awards

Discipline name	D-Index	World Ranking	Current World Ranking	National Ranking	Current National Ranking	Publications	Citations
Computer Science	31	13593	13180	5428	5165	137	4506

Rohit Prabhavalkar publication distribution in Computer Science in 2026

The chart shows the distribution of publications by all Research.com ranked scientists in the field of Computer Science in 2026. The highlighted bar marks where Rohit Prabhavalkar sits on this spectrum.

32 publications 991+

This scientist: 137 publications — 21st percentile

21% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 991 publications or more.

Rohit Prabhavalkar D-index placement in Computer Science in 2026

The chart shows the D-index (discipline H-index) distribution of Computer Science scientists ranked by Research.com in 2026. The highlighted bar marks where Rohit Prabhavalkar sits on this spectrum.

30 D-Index 131+

This scientist: 31 D-Index — 6th percentile

6% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 131 D-Index or more.

Overview

Rohit Prabhavalkar is affiliated with Google in the United States and has contributed extensively to the field of computer science, with a focus on speech and audio technologies. Their research spans core areas in artificial intelligence, signal processing, and applications of machine learning to speech recognition and synthesis.

The scientist's publication record includes works primarily centered on speech recognition systems, audio processing, and related computational techniques. Their recent papers reflect ongoing developments in automatic speech recognition (ASR), end-to-end neural models, and large-scale multilingual approaches. Notable recent publications include:

End-to-End Speech Recognition: A Survey, 2023, IEEE/ACM Transactions on Audio Speech and Language Processing
Google USM: Scaling Automatic Speech Recognition Beyond 100 Languages, 2023, arXiv (Cornell University)
E2E Segmenter: Joint Segmenting and Decoding for Long-Form ASR, 2022, Interspeech 2022
JOIST: A Joint Speech and Text Streaming Model for ASR, 2023, 2022 IEEE Spoken Language Technology Workshop (SLT)
Improving The Latency And Quality Of Cascaded Encoders, 2022, ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

Co-authorship indicates collaboration with several researchers frequently working in related fields, including:

Tara N. Sainath
Trevor Strohman
Weiran Wang
Cal Peyser
Zhong Meng

Most publications have appeared in venues specializing in speech and language processing, machine learning, and signal processing, reflecting the interdisciplinary nature of the research. These venues include:

arXiv (Cornell University)
Interspeech 2022
2022 IEEE Spoken Language Technology Workshop (SLT)
ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
IEEE/ACM Transactions on Audio Speech and Language Processing

Within the broad field of computer science, Rohit Prabhavalkar's research is concentrated in the following subfields:

Artificial Intelligence
Signal Processing
Computer Vision and Pattern Recognition
Control and Systems Engineering
Statistical and Nonlinear Physics

Their main topics of work reflect a comprehensive engagement with speech and audio technologies and include:

Speech Recognition and Synthesis
Music and Audio Processing
Speech and Audio Processing
Topic Modeling
Natural Language Processing Techniques
Speech and Dialogue Systems
Fault Detection and Control Systems

Best Publications

State-of-the-Art Speech Recognition with Sequence-to-Sequence Models

Chung-Cheng Chiu;Tara N. Sainath;Yonghui Wu;Rohit Prabhavalkar

1178
Citations
Streaming End-to-end Speech Recognition for Mobile Devices

Yanzhang He;Tara N. Sainath;Rohit Prabhavalkar;Ian McGraw

603
Citations
Exploring architectures, data and units for streaming end-to-end speech recognition with RNN-transducer

Kanishka Rao;Hasim Sak;Rohit Prabhavalkar

350
Citations
A Comparison of Sequence-to-Sequence Models for Speech Recognition

Rohit Prabhavalkar;Kanishka Rao;Tara N. Sainath;Bo Li

334
Citations
Lingvo: a Modular and Scalable Framework for Sequence-to-Sequence Modeling

Jonathan Shen;Patrick Nguyen;Yonghui Wu;Zhifeng Chen

253
Citations
An Analysis of Incorporating an External Language Model into a Sequence-to-Sequence Model

Anjuli Kannan;Yonghui Wu;Patrick Nguyen;Tara N. Sainath

234
Citations
Exploring Speech Enhancement with Generative Adversarial Networks for Robust Speech Recognition

Chris Donahue;Bo Li;Rohit Prabhavalkar

218
Citations
Personalized speech recognition on mobile devices

Ian McGraw;Rohit Prabhavalkar;Raziel Alvarez;Montse Gonzalez Arenas

202
Citations
A Streaming On-Device End-To-End Model Surpassing Server-Side Conventional Model Quality and Latency

Tara N. Sainath;Yanzhang He;Bo Li;Arun Narayanan

200
Citations
Google USM: Scaling Automatic Speech Recognition Beyond 100 Languages

Unknown

179
Citations
End-to-End Speech Recognition: A Survey

Unknown

173
Citations
Minimum Word Error Rate Training for Attention-Based Sequence-to-Sequence Models

Rohit Prabhavalkar;Tara N. Sainath;Yonghui Wu;Patrick Nguyen

153
Citations
Deep Context: End-to-end Contextual Speech Recognition

Golan Pundak;Tara N. Sainath;Rohit Prabhavalkar;Anjuli Kannan

153
Citations
From Audio to Semantics: Approaches to End-to-End Spoken Language Understanding

Parisa Haghani;Arun Narayanan;Michiel Bacchiani;Galen Chuang

138
Citations
Two-Pass End-to-End Speech Recognition

Sainath Tara C;Pang Ruoming;Rybach David;He Yanzhang

120
Citations
On the compression of recurrent neural networks with an application to LVCSR acoustic modeling for embedded speech recognition

Rohit Prabhavalkar;Ouais Alsharif;Antoine Bruguier;Lan McGraw

113
Citations
Recognizing Long-Form Speech Using Streaming End-to-End Models

Arun Narayanan;Rohit Prabhavalkar;Chung-Cheng Chiu;David Rybach

111
Citations
Automatic gain control and multi-style training for robust small-footprint keyword spotting with deep neural networks

Rohit Prabhavalkar;Raziel Alvarez;Carolina Parada;Preetum Nakkiran

102
Citations
Compressing Deep Neural Networks using a Rank-Constrained Topology

Preetum Nakkiran;Raziel Alvarez;Rohit Prabhavalkar;Carolina Parada

89
Citations
On the Compression of Recurrent Neural Networks with an Application to LVCSR acoustic modeling for Embedded Speech Recognition

Rohit Prabhavalkar;Ouais Alsharif;Antoine Bruguier;Ian McGraw

88
Citations
Streaming small-footprint keyword spotting using sequence-to-sequence models

Yanzhang He;Rohit Prabhavalkar;Kanishka Rao;Wei Li

85
Citations
State-of-the-art Speech Recognition With Sequence-to-Sequence Models

Chung-Cheng Chiu;Tara N. Sainath;Yonghui Wu;Rohit Prabhavalkar

85
Citations
A Comparison of End-to-End Models for Long-Form Speech Recognition

Chung-Cheng Chiu;Anjuli Kannan;Rohit Prabhavalkar;Zhifeng Chen

83
Citations
Deliberation Model Based Two-Pass End-To-End Speech Recognition

Ke Hu;Tara N. Sainath;Ruoming Pang;Rohit Prabhavalkar

74
Citations
Improving the Performance of Online Neural Transducer Models

Tara N. Sainath;Chung-Cheng Chiu;Rohit Prabhavalkar;Anjuli Kannan

57
Citations
Phoebe: Pronunciation-aware Contextualization for End-to-end Speech Recognition

Antoine Bruguier;Rohit Prabhavalkar;Golan Pundak;Tara N. Sainath

50
Citations
A Streaming On-Device End-to-End Model Surpassing Server-Side Conventional Model Quality and Latency

Tara N. Sainath;Yanzhang He;Bo Li;Arun Narayanan

3
Citations

Frequent Co-Authors

Tara N. Sainath Google (United States)

Chung-Cheng Chiu Google (United States)

Yonghui Wu Google (United States)

Patrick Nguyen Google (United States)

Ruoming Pang Google (United States)

Bo Li University of Illinois at Urbana-Champaign

Zhifeng Chen Google (United States)

Navdeep Jaitly Google (United States)

Michiel Bacchiani Google (United States)

Liangliang Cao Google (United States)

External Links

Personal website of Rohit Prabhavalkar

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