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Attention based end to end Speech Recognition for Voice Search in Hindi and English

2021-11-15 18:08:32
Raviraj Joshi, Venkateshan Kannan

Abstract

We describe here our work with automatic speech recognition (ASR) in the context of voice search functionality on the Flipkart e-Commerce platform. Starting with the deep learning architecture of Listen-Attend-Spell (LAS), we build upon and expand the model design and attention mechanisms to incorporate innovative approaches including multi-objective training, multi-pass training, and external rescoring using language models and phoneme based losses. We report a relative WER improvement of 15.7% on top of state-of-the-art LAS models using these modifications. Overall, we report an improvement of 36.9% over the phoneme-CTC system. The paper also provides an overview of different components that can be tuned in a LAS-based system.

Abstract (translated)

URL

https://arxiv.org/abs/2111.10208

PDF

https://arxiv.org/pdf/2111.10208.pdf


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