반응형 논문572 [2023-06-27] 오늘의 자연어처리 NoRefER: a Referenceless Quality Metric for Automatic Speech Recognition via Semi-Supervised Language Model Fine-Tuning with Contrastive Learning This paper introduces NoRefER, a novel referenceless quality metric for automatic speech recognition (ASR) systems. Traditional reference-based metrics for evaluating ASR systems require costly ground-truth transcripts. NoRefER overcomes this limitatio.. 2023. 6. 27. [2023-06-26] 오늘의 자연어처리 CamChoice: A Corpus of Multiple Choice Questions and Candidate Response Distributions Multiple Choice examinations are a ubiquitous form of assessment that is used to measure the ability of candidates across various domains and tasks. Maintaining the quality of proposed questions is of great importance to test designers, and therefore newly proposed questions go through several pre-test evaluati.. 2023. 6. 26. [2023-06-25] 오늘의 자연어처리 Instruct-FinGPT: Financial Sentiment Analysis by Instruction Tuning of General-Purpose Large Language Models Sentiment analysis is a vital tool for uncovering insights from financial articles, news, and social media, shaping our understanding of market movements. Despite the impressive capabilities of large language models (LLMs) in financial natural language processing (NLP), they still struggl.. 2023. 6. 25. [2023-06-24] 오늘의 자연어처리 Overview of Robust and Multilingual Automatic Evaluation Metrics for Open-Domain Dialogue Systems at DSTC 11 Track 4 The advent and fast development of neural networks have revolutionized the research on dialogue systems and subsequently have triggered various challenges regarding their automatic evaluation. Automatic evaluation of open-domain dialogue systems as an open challenge has been the c.. 2023. 6. 24. 이전 1 ··· 48 49 50 51 52 53 54 ··· 143 다음 반응형