Results 21 to 30 of about 460,856 (296)
Self-Supervised Speaker Embeddings [PDF]
Interspeech 2019, 2019 Preprint. Submitted to Interspeech 2019.
Themos Stafylakis +4 more
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Ordered and Binary Speaker Embedding
INTERSPEECH 2023, 2023 to be published in INTERSPEECH ...
Jiaying Wang +4 more
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ECAPA-TDNN Embeddings for Speaker Diarization [PDF]
Interspeech 2021, 2021 Learning robust speaker embeddings is a crucial step in speaker diarization. Deep neural networks can accurately capture speaker discriminative characteristics and popular deep embeddings such as x-vectors are nowadays a fundamental component of modern diarization systems.
Nauman Dawalatabad +5 more
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Emotion-Aware Speaker Identification With Transfer Learning
IEEE Access, 2023 Speech is a natural communication method used by humans. Speaker identification (SI) technology based on human speech has been used as an entry point for many human–computer-interaction applications.
Kyoungju Noh, Hyuntae Jeong
doaj +1 more source
Magnitude-Aware Probabilistic Speaker Embeddings
The Speaker and Language Recognition Workshop (Odyssey 2022), 2022 Accepted to Odyssey 2022: The Speaker and Language Recognition Workshop, camera-ready ...
Nikita Kuzmin +2 more
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A Survey on Text-Dependent and Text-Independent Speaker Verification
IEEE Access, 2022 Speaker verification (SV) aims to detect an individual’s identity from his/her voice. SV has been successfully applied in various areas such as access control, remote service customization, financial transactions, etc.
Youzhi Tu, Weiwei Lin, Man-Wai Mak
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Contrastive Speaker Embedding With Sequential Disentanglement [PDF]
, 2023 Contrastive speaker embedding assumes that the contrast between the positive and negative pairs of speech segments is attributed to speaker identity only.
Chien, Jen-Tzung +2 more
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Speaker segmentation and clustering [PDF]
, 2008 07.08.13 KB. Ok to add the accepted version to Spiral, Elsevier says ok whlile mandate not enforced.This survey focuses on two challenging speech processing topics, namely: speaker segmentation and speaker clustering. Speaker segmentation aims at finding
Kotti, Margarita +5 more
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Design of a Multi-Condition Emotional Speech Synthesizer
Applied Sciences, 2021 Recently, researchers have developed text-to-speech models based on deep learning, which have produced results superior to those of previous approaches.
Sung-Woo Byun, Seok-Pil Lee
doaj +1 more source
Phonetic-aware speaker embedding for far-field speaker verification [PDF]
, 2023 When a speaker verification (SV) system operates far from the sound sourced, significant challenges arise due to the interference of noise and reverberation.
Mak, Man-Wai, Jin, Zezhong, Tu, Youzhi
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