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20192026
most citedA Survey on Graph Neural Networks for Knowledge Graph Completion

18 citations · 44 across the 60 of their papers we have counts for

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Showing 2023 · cs.CLShow all

10 papers · 2 filters

cs.CL2023

Phoneme-aware Encoding for Prefix-tree-based Contextual ASR

Hayato Futami, Emiru Tsunoo, Yosuke Kashiwagi +3

In speech recognition applications, it is important to recognize context-specific rare words, such as proper nouns. Tree-constrained Pointer Generator (TCPGen) has shown promise fo…

cs.CL2023

Reproducing Whisper-Style Training Using an Open-Source Toolkit and Publicly Available Data

Yifan Peng, Jinchuan Tian, Brian Yan +13

Pre-training speech models on large volumes of data has achieved remarkable success. OpenAI Whisper is a multilingual multitask model trained on 680k hours of supervised speech dat…

cs.CL2023★ 1 cited

UniverSLU: Universal Spoken Language Understanding for Diverse Tasks with Natural Language Instructions

Siddhant Arora, Hayato Futami, Jee-weon Jung +6

Recent studies leverage large language models with multi-tasking capabilities, using natural language prompts to guide the model's behavior and surpassing performance of task-speci…

cs.CL2023

Semi-Autoregressive Streaming ASR With Label Context

Siddhant Arora, George Saon, Shinji Watanabe +1

Non-autoregressive (NAR) modeling has gained significant interest in speech processing since these models achieve dramatically lower inference time than autoregressive (AR) models…

cs.CL2023

Integrating Pretrained ASR and LM to Perform Sequence Generation for Spoken Language Understanding

Siddhant Arora, Hayato Futami, Yosuke Kashiwagi +3

There has been an increased interest in the integration of pretrained speech recognition (ASR) and language models (LM) into the SLU framework. However, prior methods often struggl…

cs.CL2023

BASS: Block-wise Adaptation for Speech Summarization

Roshan Sharma, Kenneth Zheng, Siddhant Arora +3

End-to-end speech summarization has been shown to improve performance over cascade baselines. However, such models are difficult to train on very large inputs (dozens of minutes or…