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20222025
most citedContextualized End-to-end Automatic Speech Recognition with Intermediate Biasing Loss

5 citations · 13 across the 14 of their papers we have counts for

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7 papers · 1 filter

eess.AS2024★ 5 cited

Contextualized End-to-end Automatic Speech Recognition with Intermediate Biasing Loss

Muhammad Shakeel, Yui Sudo, Yifan Peng +1

Contextualized end-to-end automatic speech recognition has been an active research area, with recent efforts focusing on the implicit learning of contextual phrases based on the fi…

eess.AS2024★ 2 cited

Joint Beam Search Integrating CTC, Attention, and Transducer Decoders

Yui Sudo, Muhammad Shakeel, Yosuke Fukumoto +4

End-to-end automatic speech recognition (E2E-ASR) can be classified by its decoder architectures, such as connectionist temporal classification (CTC), recurrent neural network tran…

eess.AS2024

Joint Optimization of Streaming and Non-Streaming Automatic Speech Recognition with Multi-Decoder and Knowledge Distillation

Muhammad Shakeel, Yui Sudo, Yifan Peng +1

End-to-end (E2E) automatic speech recognition (ASR) can operate in two modes: streaming and non-streaming, each with its pros and cons. Streaming ASR processes the speech frames in…

eess.AS2024

Contextualized Automatic Speech Recognition with Dynamic Vocabulary

Yui Sudo, Yosuke Fukumoto, Muhammad Shakeel +2

Deep biasing (DB) enhances the performance of end-to-end automatic speech recognition (E2E-ASR) models for rare words or contextual phrases using a bias list. However, most existin…

cs.CL2024★ 1 cited

OWSM-CTC: An Open Encoder-Only Speech Foundation Model for Speech Recognition, Translation, and Language Identification

Yifan Peng, Yui Sudo, Muhammad Shakeel +1

There has been an increasing interest in large speech models that can perform multiple tasks in a single model. Such models usually adopt an encoder-decoder or decoder-only archite…

eess.AS2024

Contextualized Automatic Speech Recognition with Attention-Based Bias Phrase Boosted Beam Search

Yui Sudo, Muhammad Shakeel, Yosuke Fukumoto +2

End-to-end (E2E) automatic speech recognition (ASR) methods exhibit remarkable performance. However, since the performance of such methods is intrinsically linked to the context pr…

cs.CL2024★ 2 cited

OWSM v3.1: Better and Faster Open Whisper-Style Speech Models based on E-Branchformer

Yifan Peng, Jinchuan Tian, William Chen +9

Recent studies have highlighted the importance of fully open foundation models. The Open Whisper-style Speech Model (OWSM) is an initial step towards reproducing OpenAI Whisper usi…