Results 11 to 20 of about 460,856 (296)
Guided Speaker Embedding [PDF]
ICASSP 2025 - 2025 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)Accepted to ICASSP ...
Shota Horiguchi +6 more
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Compact Speaker Embedding: lrx-Vector [PDF]
Interspeech 2020, 2020 Accepted to INTERSPEECH ...
Munir Georges +2 more
core +6 more sources
IET BiometricsText-independent speaker verification (TI-SV) is a crucial task in speaker recognition, as it involves verifying an individual’s claimed identity from speech of arbitrary content without any human intervention.
Xiao Li +5 more
doaj +2 more sources
Speaker embedding loss for end-to-end speaker diarization without external embedding networks
EURASIP Journal on Audio, Speech, and Music ProcessingThis paper introduces a novel speaker embedding loss function designed to improve the performance of end-to-end neural diarization (EEND) systems by enhancing speaker discrimination.
Jaehee Jung, Wooil Kim
doaj +3 more sources
Adapting Speaker Embeddings for Speaker Diarisation [PDF]
Interspeech 2021, 2021 The goal of this paper is to adapt speaker embeddings for solving the problem of speaker diarisation. The quality of speaker embeddings is paramount to the performance of speaker diarisation systems. Despite this, prior works in the field have directly used embeddings designed only to be effective on the speaker verification task.
Youngki Kwon +5 more
openaire +4 more sources
Content-Aware Speaker Embeddings for Speaker Diarisation [PDF]
ICASSP 2021 - 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2021 Recent speaker diarisation systems often convert variable length speech segments into fixed-length vector representations for speaker clustering, which are known as speaker embeddings. In this paper, the content-aware speaker embeddings (CASE) approach is proposed, which extends the input of the speaker classifier to include not only acoustic features ...
Guangzhi Sun +3 more
openaire +2 more sources
Probabilistic Embeddings for Speaker Diarization [PDF]
The Speaker and Language Recognition Workshop (Odyssey 2020), 2020 Awarded: Jack Godfrey Best Student Paper Award, at Odyssey 2020: The Speaker and Language Recognition Workshop ...
Silnova, Anna +4 more
openaire +2 more sources
Binary speaker embedding [PDF]
2016 10th International Symposium on Chinese Spoken Language Processing (ISCSLP), 2016 The popular i-vector model represents speakers as low-dimensional continuous vectors (i-vectors), and hence it is a way of continuous speaker embedding. In this paper, we investigate binary speaker embedding, which transforms i-vectors to binary vectors (codes) by a hash function.
Lantian Li +4 more
openaire +3 more sources
Speaker diarization through speaker embeddings [PDF]
2015 23rd European Signal Processing Conference (EUSIPCO), 2015 Publication in the conference proceedings of EUSIPCO, Nice, France ...
Mickael Rouvier +2 more
openaire +3 more sources
Combination of deep speaker embeddings for diarisation [PDF]
Neural Networks, 2021 Significant progress has recently been made in speaker diarisation after the introduction of d-vectors as speaker embeddings extracted from neural network (NN) speaker classifiers for clustering speech segments. To extract better-performing and more robust speaker embeddings, this paper proposes a c-vector method by combining multiple sets of ...
Guangzhi Sun +2 more
openaire +5 more sources