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RW-Resnet: A Novel Speech Anti-Spoofing Model Using Raw Waveform
In recent years, synthetic speech generated by advanced text-to-speech (TTS) and voice conversion (VC) systems has caused great harms to automatic speaker verification (ASV) systems, urging us to design a synthetic speech detection system to protect ASV systems.
A Study on Angular Based Embedding Learning for Text-independent Speaker Verification
Learning a good speaker embedding is important for many automatic speaker recognition tasks, including verification, identification and diarization.
Triplet Based Embedding Distance and Similarity Learning for Text-independent Speaker Verification
The improvements are both based on triplet cause the training stage and the evaluation stage of the baseline x-vector system focus on different aims.
Two-stage Training for Chinese Dialect Recognition
In this paper, we present a two-stage language identification (LID) system based on a shallow ResNet14 followed by a simple 2-layer recurrent neural network (RNN) architecture, which was used for Xunfei (iFlyTek) Chinese Dialect Recognition Challenge and won the first place among 110 teams.
