Harish Arsikere — accepted AI-conference papers

2025

AMuSE: Attentive Multilingual Speech Encoding for Zero-Prior ASR

Ashutosh Varshney, Debmalya Chakrabarty, Akshat Jaiswal, Harish Arsikere, Abhinav Jain, Swayambhu Nath Ray +6

ICASSP 2025accepted

Multilingual ASR offers training, deployment and overall performance benefits, but models trained via simple data pooling are known to suffer from cross-lingual interference. Oracle language information (exact-prior) and language-specific parameters are usually leveraged to overcome this, but such a…

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2021

Joint ASR and Language Identification Using RNN-T: An Efficient Approach to Dynamic Language Switching

Surabhi Punjabi, Harish Arsikere, Zeynab Raeesy, Chander Chandak, Nikhil Bhave, Ankish Bansal +10

ICASSP 2021accepted

Conventional dynamic language switching enables seamless multilingual interactions by running several monolingual ASR systems in parallel and triggering the appropriate downstream components using a standalone language identification (LID) service. Since this solution is neither scalable nor cost- a…

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2021

REDAT: Accent-Invariant Representation for End-To-End ASR by Domain Adversarial Training with Relabeling

Hu Hu, Xuesong Yang, Zeynab Raeesy, Jinxi Guo, Gokce Keskin, Harish Arsikere +3

ICASSP 2021accepted

Accents mismatching is a critical problem for end-to-end ASR. This paper aims to address this problem by building an accent-robust RNN-T system with domain adversarial training (DAT). We unveil the magic behind DAT and provide, for the first time, a theoretical guarantee that DAT learns accent-invar…

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2016

Novel acoustic features for automatic dialog-act tagging

Harish Arsikere, Arunasish Sen, A. P. Prathosh, Vivek Tyagi

ICASSP 2016accepted

This paper presents 57 new acoustic features for automatic dialog-act tagging. The features are intended to be richer than and complementary to the traditional cumulative statistics of intonation. Some of our novel contributions include feature normalization with respect to neighboring utterances, i…

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