Improving Noise Robustness for Spoken Content Retrieval Using Semi-Supervised ASR and N-Best Transcripts for BERT-Based Ranking Models-Reference-Cited by-同舟云学术

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Improving Noise Robustness for Spoken Content Retrieval Using Semi-Supervised ASR and N-Best Transcripts for BERT-Based Ranking Models

Published:2023-01-09 Issue: Volume: Page:
ISSN:
Container-title:2022 IEEE Spoken Language Technology Workshop (SLT)
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Author:

Moriya Yasufumi¹,Jones Gareth. J. F.¹

Affiliation:

1. School of Computing, Dublin City University,ADAPT Centre,Dublin 9,Ireland

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10022052/10022330/10023197.pdf?arnumber=10023197

Reference28 articles.

1. Spoken Document Retrieval Leveraging Bert-Based Modeling and Query Reformulation

2. Enhanced Bert-Based Ranking Models for Spoken Document Retrieval

3. BERT: Pre-training of deep bidirectional transform-ers for language understanding;devlin;NAACL,2019

4. Convolutional Neural Networks for Soft-Matching N-Grams in Ad-hoc Search

5. TREC 2021 podcasts track overview;jones;Text Retrieval Conference (TREC),0

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1. Evaluasi dan Implementasi Indobert Question Answering (QA) pada Domain Spesifik Menggunakan Mean Reciprocal Rank;Jurnal Algoritma;2024-05-18

2. Whisper-based spoken term detection systems for search on speech ALBAYZIN evaluation challenge;EURASIP Journal on Audio, Speech, and Music Processing;2024-02-29

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