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Found 8 papers, 2 papers with code
Shortened LLaMA: A Simple Depth Pruning for Large Language Models
Structured pruning of modern large language models (LLMs) has emerged as a way of decreasing their high computational needs.
Encoder-decoder multimodal speaker change detection
The task of speaker change detection (SCD), which detects points where speakers change in an input, is essential for several applications.
Back from the future: bidirectional CTC decoding using future information in speech recognition
In this paper, we propose a simple but effective method to decode the output of Connectionist Temporal Classifier (CTC) model using a bi-directional neural language model.
Spell my name: keyword boosted speech recognition
Recognition of uncommon words such as names and technical terminology is important to understanding conversations in context.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
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Semi-supervised Disentanglement with Independent Vector Variational Autoencoders
We aim to separate the generative factors of data into two latent vectors in a variational autoencoder.
Unpaired Speech Enhancement by Acoustic and Adversarial Supervision for Speech Recognition
Many speech enhancement methods try to learn the relationship between noisy and clean speech, obtained using an acoustic room simulator.
Deep CNNs along the Time Axis with Intermap Pooling for Robustness to Spectral Variations
Convolutional neural networks (CNNs) with convolutional and pooling operations along the frequency axis have been proposed to attain invariance to frequency shifts of features.
Compositional Sentence Representation from Character within Large Context Text
In the HCRN, word representations are built from characters, thus resolving the data-sparsity problem, and inter-sentence dependency is embedded into sentence representation at the level of sentence composition.
