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Automatic Speech Recognition

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Showing 1701–1725 of 3174 papers

TitleStatusHype
A study on native American English speech recognition by Indian listeners with varying word familiarity level—0
A Study on the Integration of Pipeline and E2E SLU systems for Spoken Semantic Parsing toward STOP Quality Challenge—0
A Study on the Integration of Pre-trained SSL, ASR, LM and SLU Models for Spoken Language Understanding—0
A study on the impact of Self-Supervised Learning on automatic dysarthric speech assessment—0
A Study on Zero-shot Non-intrusive Speech Assessment using Large Language Models—0
A Subband-Based SVM Front-End for Robust ASR—0
A Survey of Multilingual Models for Automatic Speech Recognition—0
A Survey on Speech Large Language Models—0
A Survey on Spoken Italian Datasets and Corpora—0
Asynchronous Decentralized Distributed Training of Acoustic Models—0
Asynchronous Tool Usage for Real-Time Agents—0
ATC-ANNO: Semantic Annotation for Air Traffic Control with Assistive Auto-Annotation—0
ATCSpeech: a multilingual pilot-controller speech corpus from real Air Traffic Control environment—0
ATCSpeechNet: A multilingual end-to-end speech recognition framework for air traffic control systems—0
A Text-to-Speech Pipeline, Evaluation Methodology, and Initial Fine-Tuning Results for Child Speech Synthesis—0
A Toolkit for Joint Speaker Diarization and Identification with Application to Speaker-Attributed ASR—0
The ILMT-s2s Corpus ― A Multimodal Interlingual Map Task Corpus—0
The Impact of Code-switched Synthetic Data Quality is Task Dependent: Insights from MT and ASR—0
The Indigenous Languages Technology project at NRC Canada: An empowerment-oriented approach to developing language software—0
The IWSLT 2016 Evaluation Campaign—0
The IWSLT 2021 BUT Speech Translation Systems—0
The JHU Multi-Microphone Multi-Speaker ASR System for the CHiME-6 Challenge—0
The Makerere Radio Speech Corpus: A Luganda Radio Corpus for Automatic Speech Recognition—0
The MeMAD Submission to the IWSLT 2018 Speech Translation Task—0
The Multicultural Medical Assistant: Can LLMs Improve Medical ASR Errors Across Borders?—0
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