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Overview of speaker modeling and its applications: From the lens of deep speaker representation learning
Speaker individuality information is among the most critical elements within speech signals.
By thoroughly and accurately modeling this information, it can be utilized in various …
By thoroughly and accurately modeling this information, it can be utilized in various …
**-vector embedding for speaker recognition
We present a Bayesian formulation for deep speaker embedding, wherein the xi-vector is
the Bayesian counterpart of the x-vector, taking into account the uncertainty estimate. On the …
the Bayesian counterpart of the x-vector, taking into account the uncertainty estimate. On the …
SpeakerNet: 1D depth-wise separable convolutional network for text-independent speaker recognition and verification
We propose SpeakerNet-a new neural architecture for speaker recognition and speaker
verification tasks. It is composed of residual blocks with 1D depth-wise separable …
verification tasks. It is composed of residual blocks with 1D depth-wise separable …
Target speaker verification with selective auditory attention for single and multi-talker speech
Speaker verification has been studied mostly under the single-talker condition. It is
adversely affected in the presence of interference speakers. Inspired by the study on target …
adversely affected in the presence of interference speakers. Inspired by the study on target …
Understanding self-attention of self-supervised audio transformers
Self-supervised Audio Transformers (SAT) enable great success in many downstream
speech applications like ASR, but how they work has not been widely explored yet. In this …
speech applications like ASR, but how they work has not been widely explored yet. In this …
Robust speaker recognition using speech enhancement and attention model
In this paper, a novel architecture for speaker recognition is proposed by cascading speech
enhancement and speaker processing. Its aim is to improve speaker recognition …
enhancement and speaker processing. Its aim is to improve speaker recognition …
H-vectors: Utterance-level speaker embedding using a hierarchical attention model
In this paper, a hierarchical attention network is proposed to generate utterance-level
embeddings (H-vectors) for speaker identification and verification. Since different parts of an …
embeddings (H-vectors) for speaker identification and verification. Since different parts of an …
A unified deep learning framework for short-duration speaker verification in adverse environments
Speaker verification (SV) has recently attracted considerable research interest due to the
growing popularity of virtual assistants. At the same time, there is an increasing requirement …
growing popularity of virtual assistants. At the same time, there is an increasing requirement …
Discriminative speaker embedding with serialized multi-layer multi-head attention
In this paper, a serialized multi-layer multi-head attention is proposed for extracting neural
speaker embedding in text-independent speaker verification task. The majority of the recent …
speaker embedding in text-independent speaker verification task. The majority of the recent …
Combination of deep speaker embeddings for diarisation
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 …
vectors as speaker embeddings extracted from neural network (NN) speaker classifiers for …