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Found 6 papers, 1 papers with code
Transformer versus LSTM Language Models trained on Uncertain ASR Hypotheses in Limited Data Scenarios
Training of LSTM LMs in such limited data scenarios can benefit from alternate uncertain ASR hypotheses, as observed in our recent work.
A Cycle-GAN Approach to Model Natural Perturbations in Speech for ASR Applications
Naturally introduced perturbations in audio signal, caused by emotional and physical states of the speaker, can significantly degrade the performance of Automatic Speech Recognition (ASR) systems.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+2
Sentiment Analysis using Imperfect Views from Spoken Language and Acoustic Modalities
Multimodal sentiment classification in practical applications may have to rely on erroneous and imperfect views, namely (a) language transcription from a speech recognizer and (b) under-performing acoustic views.
Automatic Speech Recognition (ASR)
General Classification
+2
How Diachronic Text Corpora Affect Context based Retrieval of OOV Proper Names for Audio News
Out-Of-Vocabulary (OOV) words missed by Large Vocabulary Continuous Speech Recognition (LVCSR) systems can be recovered with the help of topic and semantic context of the OOV words captured from a diachronic text corpus.
Learning to retrieve out-of-vocabulary words in speech recognition
In this paper, we propose two neural network models targeted to retrieve OOV PNs relevant to an audio document: (a) Document level Continuous Bag of Words (D-CBOW), (b) Document level Continuous Bag of Weighted Words (D-CBOW2).
