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Found 5 papers, 0 papers with code
Effective Cross-Utterance Language Modeling for Conversational Speech Recognition
Conversational speech normally is embodied with loose syntactic structures at the utterance level but simultaneously exhibits topical coherence relations across consecutive utterances.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+2
Cross-utterance Reranking Models with BERT and Graph Convolutional Networks for Conversational Speech Recognition
In view of this, we in this paper seek to represent the historical context information of an utterance as graph-structured data so as to distill cross-utterances, global word interaction relationships.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+3
Innovative Bert-based Reranking Language Models for Speech Recognition
More recently, Bidirectional Encoder Representations from Transformers (BERT) was proposed and has achieved impressive success on many natural language processing (NLP) tasks such as question answering and language understanding, due mainly to its effective pre-training then fine-tuning paradigm as well as strong local contextual modeling ability.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+2
The NTNU Taiwanese ASR System for Formosa Speech Recognition Challenge 2020
This paper describes the NTNU ASR system participating in the Formosa Speech Recognition Challenge 2020 (FSR-2020) supported by the Formosa Speech in the Wild project (FSW).
