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Found 9 papers, 0 papers with code
Turn-taking and Backchannel Prediction with Acoustic and Large Language Model Fusion
We propose an approach for continuous prediction of turn-taking and backchanneling locations in spoken dialogue by fusing a neural acoustic model with a large language model (LLM).
Guided contrastive self-supervised pre-training for automatic speech recognition
Contrastive Predictive Coding (CPC) is a representation learning method that maximizes the mutual information between intermediate latent representations and the output of a given model.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+2
Do You Listen with One or Two Microphones? A Unified ASR Model for Single and Multi-Channel Audio
An ASR model that operates on both primary and auxiliary data can achieve better accuracy compared to a primary-only solution; and a model that can serve both primary-only (PO) and primary-plus-auxiliary (PPA) modes is highly desirable.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+1
Listen with Intent: Improving Speech Recognition with Audio-to-Intent Front-End
On the other hand, a streaming system using per-frame intent posteriors as extra inputs for the RNN-T ASR system yields a 3. 33% relative WERR.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+1
Attention-based Neural Beamforming Layers for Multi-channel Speech Recognition
The end-to-end 2D Conv-Attention model is compared with a multi-head self-attention and superdirective-based neural beamformers.
Wav2vec-C: A Self-supervised Model for Speech Representation Learning
However, the quantization process is regularized by an additional consistency network that learns to reconstruct the input features to the wav2vec 2. 0 network from the quantized representations in a way similar to a VQ-VAE model.
Robust Multi-channel Speech Recognition using Frequency Aligned Network
In this paper, we further develop this idea and use frequency aligned network for robust multi-channel automatic speech recognition (ASR).
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+2
Fully Learnable Front-End for Multi-Channel Acoustic Modeling using Semi-Supervised Learning
Using a large offline teacher model trained on beamformed audio, we trained a simpler multi-channel student acoustic model used in the speech recognition system.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+1
Improving noise robustness of automatic speech recognition via parallel data and teacher-student learning
For real-world speech recognition applications, noise robustness is still a challenge.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+1
