Search Results for author: Chaitanya Narisetty

Found 6 papers, 1 papers with code

Residual Language Model for End-to-end Speech Recognition

no code implementations15 Jun 2022 Emiru Tsunoo, Yosuke Kashiwagi, Chaitanya Narisetty, Shinji Watanabe

In this paper, we propose a simple external LM fusion method for domain adaptation, which considers the internal LM estimation in its training.

Automatic Speech Recognition Domain Adaptation +1

Joint Speech Recognition and Audio Captioning

no code implementations3 Feb 2022 Chaitanya Narisetty, Emiru Tsunoo, Xuankai Chang, Yosuke Kashiwagi, Michael Hentschel, Shinji Watanabe

A major hurdle in evaluating our proposed approach is the lack of labeled audio datasets with both speech transcriptions and audio captions.

Audio captioning Automatic Speech Recognition +2

Run-and-back stitch search: novel block synchronous decoding for streaming encoder-decoder ASR

no code implementations25 Jan 2022 Emiru Tsunoo, Chaitanya Narisetty, Michael Hentschel, Yosuke Kashiwagi, Shinji Watanabe

To this end, we propose a novel blockwise synchronous decoding algorithm with a hybrid approach that combines endpoint prediction and endpoint post-determination.

Automatic Speech Recognition speech-recognition

SAPPHIRE: Approaches for Enhanced Concept-to-Text Generation

1 code implementation INLG (ACL) 2021 Steven Y. Feng, Jessica Huynh, Chaitanya Narisetty, Eduard Hovy, Varun Gangal

We motivate and propose a suite of simple but effective improvements for concept-to-text generation called SAPPHIRE: Set Augmentation and Post-hoc PHrase Infilling and REcombination.

Concept-To-Text Generation

Data Augmentation Methods for End-to-end Speech Recognition on Distant-Talk Scenarios

no code implementations7 Jun 2021 Emiru Tsunoo, Kentaro Shibata, Chaitanya Narisetty, Yosuke Kashiwagi, Shinji Watanabe

Although end-to-end automatic speech recognition (E2E ASR) has achieved great performance in tasks that have numerous paired data, it is still challenging to make E2E ASR robust against noisy and low-resource conditions.

Automatic Speech Recognition Data Augmentation +2

Bayesian Non-Parametric Multi-Source Modelling Based Determined Blind Source Separation

no code implementations8 Apr 2019 Chaitanya Narisetty, Tatsuya Komatsu, Reishi Kondo

This paper proposes a determined blind source separation method using Bayesian non-parametric modelling of sources.

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