Speaker recognition based on deep learning: An overview
Speaker recognition is a task of identifying persons from their voices. Recently, deep
learning has dramatically revolutionized speaker recognition. However, there is lack of …
learning has dramatically revolutionized speaker recognition. However, there is lack of …
A review of speaker diarization: Recent advances with deep learning
Speaker diarization is a task to label audio or video recordings with classes that correspond
to speaker identity, or in short, a task to identify “who spoke when”. In the early years …
to speaker identity, or in short, a task to identify “who spoke when”. In the early years …
Bayesian hmm clustering of x-vector sequences (vbx) in speaker diarization: theory, implementation and analysis on standard tasks
The recently proposed VBx diarization method uses a Bayesian hidden Markov model to
find speaker clusters in a sequence of x-vectors. In this work we perform an extensive …
find speaker clusters in a sequence of x-vectors. In this work we perform an extensive …
End-to-end speaker diarization for an unknown number of speakers with encoder-decoder based attractors
End-to-end speaker diarization for an unknown number of speakers is addressed in this
paper. Recently proposed end-to-end speaker diarization outperformed conventional …
paper. Recently proposed end-to-end speaker diarization outperformed conventional …
Integration of speech separation, diarization, and recognition for multi-speaker meetings: System description, comparison, and analysis
Multi-speaker speech recognition of unsegmented recordings has diverse applications such
as meeting transcription and automatic subtitle generation. With technical advances in …
as meeting transcription and automatic subtitle generation. With technical advances in …
Dover-lap: A method for combining overlap-aware diarization outputs
Several advances have been made recently towards handling overlapping speech for
speaker diarization. Since speech and natural language tasks often benefit from ensemble …
speaker diarization. Since speech and natural language tasks often benefit from ensemble …
Encoder-decoder based attractors for end-to-end neural diarization
This paper investigates an end-to-end neural diarization (EEND) method for an unknown
number of speakers. In contrast to the conventional cascaded approach to speaker …
number of speakers. In contrast to the conventional cascaded approach to speaker …
Multi-channel conversational speaker separation via neural diarization
H Taherian, DL Wang - IEEE/ACM Transactions on Audio …, 2024 - ieeexplore.ieee.org
When dealing with overlapped speech, the performance of automatic speech recognition
(ASR) systems substantially degrades as they are designed for single-talker speech. To …
(ASR) systems substantially degrades as they are designed for single-talker speech. To …
Advances in integration of end-to-end neural and clustering-based diarization for real conversational speech
Recently, we proposed a novel speaker diarization method called End-to-End-Neural-
Diarization-vector clustering (EEND-vector clustering) that integrates clustering-based and …
Diarization-vector clustering (EEND-vector clustering) that integrates clustering-based and …
Ava-avd: Audio-visual speaker diarization in the wild
Audio-visual speaker diarization aims at detecting" who spoke when''using both auditory
and visual signals. Existing audio-visual diarization datasets are mainly focused on indoor …
and visual signals. Existing audio-visual diarization datasets are mainly focused on indoor …