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Found 11 papers, 1 papers with code
A Preliminary Study on Automated Speaking Assessment of English as a Second Language (ESL) Students
Due to the surge in global demand for English as a second language (ESL), developments of automated methods for grading speaking proficiency have gained considerable attention.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+1
An Effective Automated Speaking Assessment Approach to Mitigating Data Scarcity and Imbalanced Distribution
Automated speaking assessment (ASA) typically involves automatic speech recognition (ASR) and hand-crafted feature extraction from the ASR transcript of a learner's speech.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+2
A Hierarchical Context-aware Modeling Approach for Multi-aspect and Multi-granular Pronunciation Assessment
Automatic Pronunciation Assessment (APA) plays a vital role in Computer-assisted Pronunciation Training (CAPT) when evaluating a second language (L2) learner's speaking proficiency.
Maximum F1-score training for end-to-end mispronunciation detection and diagnosis of L2 English speech
End-to-end (E2E) neural models are increasingly attracting attention as a promising modeling approach for mispronunciation detection and diagnosis (MDD).
Cross-domain Single-channel Speech Enhancement Model with Bi-projection Fusion Module for Noise-robust ASR
In recent decades, many studies have suggested that phase information is crucial for speech enhancement (SE), and time-domain single-channel speech enhancement techniques have shown promise in noise suppression and robust automatic speech recognition (ASR).
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+2
TENET: A Time-reversal Enhancement Network for Noise-robust ASR
Due to the unprecedented breakthroughs brought about by deep learning, speech enhancement (SE) techniques have been developed rapidly and play an important role prior to acoustic modeling to mitigate noise effects on speech.
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
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).
The NTNU System at the Interspeech 2020 Non-Native Children's Speech ASR Challenge
This paper describes the NTNU ASR system participating in the Interspeech 2020 Non-Native Children's Speech ASR Challenge supported by the SIG-CHILD group of ISCA.
