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A Study on Contextualized Language Modeling for Machine Reading Comprehension
With the recent breakthrough of deep learning technologies, research on machine reading comprehension (MRC) has attracted much attention and found its versatile applications in many use cases.
Exploring the Integration of E2E ASR and Pronunciation Modeling for English Mispronunciation Detection
In the first stage, the speech uttered by an L2 learner is processed by an end-to-end ASR module to produce N-best phone sequence hypotheses.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
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Building an Enhanced Autoregressive Document Retriever Leveraging Supervised Contrastive Learning
DSI dramatically simplifies the whole retrieval process by encoding all information about the document collection into the parameter space of a single Transformer model, on top of which DSI can in turn generate the relevant document identities (IDs) in an autoregressive manner in response to a user query.
Exploring Non-Autoregressive End-To-End Neural Modeling For English Mispronunciation Detection And Diagnosis
In addition, we design and develop a pronunciation modeling network stacked on top of the NAR E2E models of our method to further boost the effectiveness of MD&D.
Effective FAQ Retrieval and Question Matching With Unsupervised Knowledge Injection
To this end, predominant approaches to FAQ retrieval typically rank question-answer pairs by considering either the similarity between the query and a question (q-Q), the relevance between the query and the associated answer of a question (q-A), or combining the clues gathered from the q-Q similarity measure and the q-A relevance measure.
