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Found 6 papers, 0 papers with code
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.
Multi-Stream End-to-End Speech Recognition
Two representative framework have been proposed and discussed, which are Multi-Encoder Multi-Resolution (MEM-Res) framework and Multi-Encoder Multi-Array (MEM-Array) framework, respectively.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+1
Multi-encoder multi-resolution framework for end-to-end speech recognition
In this work, we present a novel Multi-Encoder Multi-Resolution (MEMR) framework based on the joint CTC/Attention model.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+1
Multilingual sequence-to-sequence speech recognition: architecture, transfer learning, and language modeling
In this work, we attempt to use data from 10 BABEL languages to build a multi-lingual seq2seq model as a prior model, and then port them towards 4 other BABEL languages using transfer learning approach.
Device-directed Utterance Detection
In this work, we propose a classifier for distinguishing device-directed queries from background speech in the context of interactions with voice assistants.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+2
On the Relevance of Auditory-Based Gabor Features for Deep Learning in Automatic Speech Recognition
Previous studies support the idea of merging auditory-based Gabor features with deep learning architectures to achieve robust automatic speech recognition, however, the cause behind the gain of such combination is still unknown.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+2
