Search Results for author:
Found 6 papers, 2 papers with code
SPGM: Prioritizing Local Features for enhanced speech separation performance
Dual-path is a popular architecture for speech separation models (e. g. Sepformer) which splits long sequences into overlapping chunks for its intra- and inter-blocks that separately model intra-chunk local features and inter-chunk global relationships.
Ranked #5 on
Speech Separation
on WSJ0-2mix
ACA-Net: Towards Lightweight Speaker Verification using Asymmetric Cross Attention
In this paper, we propose ACA-Net, a lightweight, global context-aware speaker embedding extractor for Speaker Verification (SV) that improves upon existing work by using Asymmetric Cross Attention (ACA) to replace temporal pooling.
Adaptive Knowledge Distillation between Text and Speech Pre-trained Models
Learning on a massive amount of speech corpus leads to the recent success of many self-supervised speech models.
Amino Acid Classification in 2D NMR Spectra via Acoustic Signal Embeddings
Nuclear Magnetic Resonance (NMR) is used in structural biology to experimentally determine the structure of proteins, which is used in many areas of biology and is an important part of drug development.
On the Effectiveness of Pinyin-Character Dual-Decoding for End-to-End Mandarin Chinese ASR
Based on the above intuition, we first investigate types of end-to-end encoder-decoder based models in the single-input dual-output (SIDO) multi-task framework, after which a novel asynchronous decoding with fuzzy Pinyin sampling method is proposed according to the one-to-one correspondence characteristics between Pinyin and Character.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+2
Intra-Inter Subject Self-supervised Learning for Multivariate Cardiac Signals
In inter subject self-supervision, we design a set of data augmentations according to the clinical characteristics of cardiac signals and perform contrastive learning among subjects to learn distinctive representations for various types of patients.
