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Found 7 papers, 1 papers with code
Multilingual Graphemic Hybrid ASR with Massive Data Augmentation
Towards developing high-performing ASR for low-resource languages, approaches to address the lack of resources are to make use of data from multiple languages, and to augment the training data by creating acoustic variations.
Training ASR models by Generation of Contextual Information
Supervised ASR models have reached unprecedented levels of accuracy, thanks in part to ever-increasing amounts of labelled training data.
Large scale weakly and semi-supervised learning for low-resource video ASR
Many semi- and weakly-supervised approaches have been investigated for overcoming the labeling cost of building high quality speech recognition systems.
A Multi-View Approach To Audio-Visual Speaker Verification
Although speaker verification has conventionally been an audio-only task, some practical applications provide both audio and visual streams of input.
Improved Language Identification Through Cross-Lingual Self-Supervised Learning
Language identification greatly impacts the success of downstream tasks such as automatic speech recognition.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+3
Conformer-Based Self-Supervised Learning for Non-Speech Audio Tasks
While self-supervised speech representation learning has been popular in the speech research community, very few works have comprehensively analyzed audio representation learning for non-speech audio tasks.
Ranked #5 on
Audio Classification
on Balanced Audio Set
XLS-R: Self-supervised Cross-lingual Speech Representation Learning at Scale
On the CoVoST-2 speech translation benchmark, we improve the previous state of the art by an average of 7. 4 BLEU over 21 translation directions into English.
Ranked #1 on
Language Identification
on VoxLingua107
(using extra training data)
