Speaker diarization has gained considerable attention within speech
proc...
This paper presents FunCodec, a fundamental neural speech codec toolkit,...
We introduce UbiPhysio, a milestone framework that delivers fine-grained...
Training speaker-discriminative and robust speaker verification systems
...
Transformer-based pre-trained language models, such as BERT, achieve gre...
Disentangling uncorrelated information in speech utterances is a crucial...
Speaker diarization(SD) is a classic task in speech processing and is cr...
Effective fusion of multi-scale features is crucial for improving speake...
Prior studies diagnose the anisotropy problem in sentence representation...
Time delay neural network (TDNN) has been proven to be efficient for spe...
The goal of expressive Text-to-speech (TTS) is to synthesize natural spe...
Recently, hybrid systems of clustering and neural diarization models hav...
Training robust speaker verification systems without speaker labels has ...
Speaker embedding has been a fundamental feature for speaker-related tas...
Clustering-based speaker diarization has stood firm as one of the major
...
Unsupervised clustering on speakers is becoming increasingly important f...
Overlapping speech diarization has been traditionally treated as a
multi...
The ICASSP 2022 Multi-channel Multi-party Meeting Transcription Grand
Ch...
Overlapping speech diarization is always treated as a multi-label
classi...
Recent development of speech signal processing, such as speech recogniti...
Transformer-based models have achieved great success in various NLP, vis...
We propose BeamTransformer, an efficient architecture to leverage
beamfo...
COVID-19, as a global health crisis, has triggered the fear emotion with...
In this paper we describe a speaker diarization system that enables
loca...
Estimating health benefits of reducing fossil fuel use from improved air...