Word spotting, VAD, and other topics in speech recognition

FEDERATED LEARNING FOR ASR BASED ON WAV2VEC 2.0

The DKU Post-Challenge Audio-Visual Wake Word Spotting System for the 2021 MISP Challenge: Deep Analysis

Joint unsupervised and supervised learning for context-aware language identification

Neural Diarization with Non-autoregressive Intermediate Attractors

WeKws: A production first small-footprint end-to-end Keyword Spotting Toolkit

Peak-First CTC: Reducing the Peak Latency of CTC Models by Applying Peak-First Regularization

Exploring Sequence-to-Sequence Transformer-Transducer Models for Keyword Spotting

Self-supervised speech representation learning for keyword-spotting with light-weight transformers

Conversation-oriented ASR with multi-look-ahead CBS architecture

Lightweight feature encoder for wake-up word detection based on self-supervised speech representation

VE-KWS: VISUAL MODALITY ENHANCED END-TO-END KEYWORD SPOTTING

E2E Segmentation in a Two-Pass Cascaded Encoder ASR Model