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[PDF][PDF] Effects of Data Resampling on Predicting Customer Churn via a Comparative Tree-based Random Forest and XGBoost
Customer attrition has become the focus of many businesses today–since the online market
space has continued to proffer customers, various choices and alternatives to goods …
space has continued to proffer customers, various choices and alternatives to goods …
Gradient remedy for multi-task learning in end-to-end noise-robust speech recognition
Speech enhancement (SE) is proved effective in reducing noise from noisy speech signals
for downstream automatic speech recognition (ASR), where multi-task learning strategy is …
for downstream automatic speech recognition (ASR), where multi-task learning strategy is …
Speech separation with pretrained frontend to minimize domain mismatch
Speech separation seeks to separate individual speech signals from a speech mixture.
Typically, most separation models are trained on synthetic data due to the unavailability of …
Typically, most separation models are trained on synthetic data due to the unavailability of …
Learning video temporal dynamics with cross-modal attention for robust audio-visual speech recognition
Audio-visual speech recognition (AVSR) aims to transcribe human speech using both audio
and video modalities. In practical environments with noise-corrupted audio, the role of video …
and video modalities. In practical environments with noise-corrupted audio, the role of video …
Selective huBERT: Self-supervised pre-training for target speaker in clean and mixture speech
Self-supervised pre-trained speech models were shown effective for various downstream
speech processing tasks. Since they are mainly pre-trained to map input speech to pseudo …
speech processing tasks. Since they are mainly pre-trained to map input speech to pseudo …
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 …
extractor for Speaker Verification (SV) that improves upon existing work by using Asymmetric …
[PDF][PDF] Dual-memory multimodal learning for continual spoken keyword spotting with confidence selection and diversity enhancement
Enabling continual learning (CL) from an ever-changing environment is highly valuable, but
it poses significant challenges for spoken keyword spotting (KWS), which simultaneously …
it poses significant challenges for spoken keyword spotting (KWS), which simultaneously …
[HTML][HTML] Environment-aware knowledge distillation for improved resource-constrained edge speech recognition
Recent advances in self-supervised learning have allowed automatic speech recognition
(ASR) systems to achieve state-of-the-art (SOTA) word error rates (WER) while requiring …
(ASR) systems to achieve state-of-the-art (SOTA) word error rates (WER) while requiring …
R-Spin: Efficient Speaker and Noise-invariant Representation Learning with Acoustic Pieces
This paper introduces Robust Spin (R-Spin), a data-efficient domain-specific self-
supervision method for speaker and noise-invariant speech representations by learning …
supervision method for speaker and noise-invariant speech representations by learning …
Are Soft Prompts Good Zero-Shot Learners for Speech Recognition?
Large self-supervised pre-trained speech models require computationally expensive fine-
tuning for downstream tasks. Soft prompt tuning offers a simple parameter-efficient …
tuning for downstream tasks. Soft prompt tuning offers a simple parameter-efficient …