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Automatic speech recognition using advanced deep learning approaches: A survey
Recent advancements in deep learning (DL) have posed a significant challenge for
automatic speech recognition (ASR). ASR relies on extensive training datasets, including …
automatic speech recognition (ASR). ASR relies on extensive training datasets, including …
Using transformers for multimodal emotion recognition: Taxonomies and state of the art review
Emotion recognition is an aspect of human-computer interaction, affective computing, and
social robotics. Conventional unimodal approaches for emotion recognition, depending on …
social robotics. Conventional unimodal approaches for emotion recognition, depending on …
End-to-end speech recognition: A survey
In the last decade of automatic speech recognition (ASR) research, the introduction of deep
learning has brought considerable reductions in word error rate of more than 50% relative …
learning has brought considerable reductions in word error rate of more than 50% relative …
Transvg: End-to-end visual grounding with transformers
In this paper, we present a neat yet effective transformer-based framework for visual
grounding, namely TransVG, to address the task of grounding a language query to the …
grounding, namely TransVG, to address the task of grounding a language query to the …
Conformer: Convolution-augmented transformer for speech recognition
A Gulati, J Qin, CC Chiu, N Parmar, Y Zhang… - ar** real-time streaming transformer transducer for speech recognition on large-scale dataset
Recently, Transformer based end-to-end models have achieved great success in many
areas including speech recognition. However, compared to LSTM models, the heavy …
areas including speech recognition. However, compared to LSTM models, the heavy …