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20212024
most citedA Real-time Speaker Diarization System Based on Spatial Spectrum

17 citations · 49 across the 24 of their papers we have counts for

collaborators

24 papers

eess.AS2024★ 1 cited

Self-Distillation Prototypes Network: Learning Robust Speaker Representations without Supervision

Yafeng Chen, Siqi Zheng, Hui Wang +4

Training speaker-discriminative and robust speaker verification systems without explicit speaker labels remains a persisting challenge. In this paper, we propose a new self-supervi…

cs.SD2023★ 2 cited

Improving Speaker Diarization using Semantic Information: Joint Pairwise Constraints Propagation

Luyao Cheng, Siqi Zheng, Qinglin Zhang +4

Speaker diarization has gained considerable attention within speech processing research community. Mainstream speaker diarization rely primarily on speakers' voice characteristics…

eess.AS2023

Self-Distillation Prototypes Network: Learning Robust Speaker Representations without Supervision

Yafeng Chen, Siqi Zheng, Hui Wang +5

Training speaker-discriminative and robust speaker verification systems without explicit speaker labels remains a persistent challenge. In this paper, we propose a novel self-super…

cs.CL2023

Improving BERT with Hybrid Pooling Network and Drop Mask

Qian Chen, Wen Wang, Qinglin Zhang +3

Transformer-based pre-trained language models, such as BERT, achieve great success in various natural language understanding tasks. Prior research found that BERT captures a rich h…

cs.CL2023★ 5 cited

3D-Speaker: A Large-Scale Multi-Device, Multi-Distance, and Multi-Dialect Corpus for Speech Representation Disentanglement

Siqi Zheng, Luyao Cheng, Yafeng Chen +2

Disentangling uncorrelated information in speech utterances is a crucial research topic within speech community. Different speech-related tasks focus on extracting distinct speech…

cs.CL2023

Exploring Speaker-Related Information in Spoken Language Understanding for Better Speaker Diarization

Luyao Cheng, Siqi Zheng, Zhang Qinglin +3

Speaker diarization(SD) is a classic task in speech processing and is crucial in multi-party scenarios such as meetings and conversations. Current mainstream speaker diarization ap…

eess.AS2023★ 3 cited

An Enhanced Res2Net with Local and Global Feature Fusion for Speaker Verification

Yafeng Chen, Siqi Zheng, Hui Wang +3

Effective fusion of multi-scale features is crucial for improving speaker verification performance. While most existing methods aggregate multi-scale features in a layer-wise manne…

cs.CL2023

Ditto: A Simple and Efficient Approach to Improve Sentence Embeddings

Qian Chen, Wen Wang, Qinglin Zhang +6

Prior studies diagnose the anisotropy problem in sentence representations from pre-trained language models, e.g., BERT, without fine-tuning. Our analysis reveals that the sentence…

cs.SD2023★ 3 cited

CAM++: A Fast and Efficient Network for Speaker Verification Using Context-Aware Masking

Hui Wang, Siqi Zheng, Yafeng Chen +2

Time delay neural network (TDNN) has been proven to be efficient for speaker verification. One of its successful variants, ECAPA-TDNN, achieved state-of-the-art performance at the…

eess.AS2022

DopplerBAS: Binaural Audio Synthesis Addressing Doppler Effect

Jinglin Liu, Zhenhui Ye, Qian Chen +4

Recently, binaural audio synthesis (BAS) has emerged as a promising research field for its applications in augmented and virtual realities. Binaural audio helps users orient themse…

eess.AS2022

Contextual Expressive Text-to-Speech

Jianhong Tu, Zeyu Cui, Xiaohuan Zhou +4

The goal of expressive Text-to-speech (TTS) is to synthesize natural speech with desired content, prosody, emotion, or timbre, in high expressiveness. Most of previous studies atte…

cs.SD2022★ 1 cited

Speaker Overlap-aware Neural Diarization for Multi-party Meeting Analysis

Zhihao Du, Shiliang Zhang, Siqi Zheng +1

Recently, hybrid systems of clustering and neural diarization models have been successfully applied in multi-party meeting analysis. However, current models always treat overlapped…

eess.AS2022

Pushing the limits of self-supervised speaker verification using regularized distillation framework

Yafeng Chen, Siqi Zheng, Hui Wang +2

Training robust speaker verification systems without speaker labels has long been a challenging task. Previous studies observed a large performance gap between self-supervised and…

cs.SD2022

PRISM: Pre-trained Indeterminate Speaker Representation Model for Speaker Diarization and Speaker Verification

Siqi Zheng, Hongbin Suo, Qian Chen

Speaker embedding has been a fundamental feature for speaker-related tasks such as verification, clustering, and diarization. Traditionally, speaker embeddings are represented as f…

eess.AS2022

Deep Representation Decomposition for Rate-Invariant Speaker Verification

Fuchuan Tong, Siqi Zheng, Haodong Zhou +3

While promising performance for speaker verification has been achieved by deep speaker embeddings, the advantage would reduce in the case of speaking-style variability. Speaking ra…

cs.SD2022

Reformulating Speaker Diarization as Community Detection With Emphasis On Topological Structure

Siqi Zheng, Hongbin Suo

Clustering-based speaker diarization has stood firm as one of the major approaches in reality, despite recent development in end-to-end diarization. However, clustering methods hav…

eess.AS2022

Graph Convolutional Network Based Semi-Supervised Learning on Multi-Speaker Meeting Data

Fuchuan Tong, Siqi Zheng, Min Zhang +4

Unsupervised clustering on speakers is becoming increasingly important for its potential uses in semi-supervised learning. In reality, we are often presented with enormous amounts…

cs.SD2022★ 1 cited

Speaker Embedding-aware Neural Diarization: an Efficient Framework for Overlapping Speech Diarization in Meeting Scenarios

Zhihao Du, Shiliang Zhang, Siqi Zheng +1

Overlapping speech diarization has been traditionally treated as a multi-label classification problem. In this paper, we reformulate this task as a single-label prediction problem…

cs.SD2022

Summary On The ICASSP 2022 Multi-Channel Multi-Party Meeting Transcription Grand Challenge

Fan Yu, Shiliang Zhang, Pengcheng Guo +13

The ICASSP 2022 Multi-channel Multi-party Meeting Transcription Grand Challenge (M2MeT) focuses on one of the most valuable and the most challenging scenarios of speech technologie…

cs.SD2021★ 1 cited

Speaker Embedding-aware Neural Diarization for Flexible Number of Speakers with Textual Information

Zhihao Du, Shiliang Zhang, Siqi Zheng +2

Overlapping speech diarization is always treated as a multi-label classification problem. In this paper, we reformulate this task as a single-label prediction problem by encoding t…

cs.SD2021★ 11 cited

M2MeT: The ICASSP 2022 Multi-Channel Multi-Party Meeting Transcription Challenge

Fan Yu, Shiliang Zhang, Yihui Fu +9

Recent development of speech processing, such as speech recognition, speaker diarization, etc., has inspired numerous applications of speech technologies. The meeting scenario is o…

cs.CL2021★ 4 cited

PoNet: Pooling Network for Efficient Token Mixing in Long Sequences

Chao-Hong Tan, Qian Chen, Wen Wang +3

Transformer-based models have achieved great success in various NLP, vision, and speech tasks. However, the core of Transformer, the self-attention mechanism, has a quadratic time…

cs.SD2021

BeamTransformer: Microphone Array-based Overlapping Speech Detection

Siqi Zheng, Shiliang Zhang, Weilong Huang +5

We propose BeamTransformer, an efficient architecture to leverage beamformer's edge in spatial filtering and transformer's capability in context sequence modeling. BeamTransformer…

cs.SD2021★ 17 cited

A Real-time Speaker Diarization System Based on Spatial Spectrum

Siqi Zheng, Weilong Huang, Xianliang Wang +3

In this paper we describe a speaker diarization system that enables localization and identification of all speakers present in a conversation or meeting. We propose a novel systema…