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eess.AS2025★ 1 cited
Better Pseudo-labeling with Multi-ASR Fusion and Error Correction by SpeechLLM
Jeena Prakash, Blessingh Kumar, Kadri Hacioglu +5
Automatic speech recognition (ASR) models rely on high-quality transcribed data for effective training. Generating pseudo-labels for large unlabeled audio datasets often relies on…
eess.AS2023
On the Efficacy and Noise-Robustness of Jointly Learned Speech Emotion and Automatic Speech Recognition
Lokesh Bansal, S. Pavankumar Dubagunta, Malolan Chetlur +2
New-age conversational agent systems perform both speech emotion recognition (SER) and automatic speech recognition (ASR) using two separate and often independent approaches for re…