2 citations · 5 across the 19 of their papers we have counts for
23 papers
B-GRPO: Unsupervised Speech Emotion Recognition based on Batched-Group Relative Policy Optimization
Yingying Gao, Shilei Zhang, Runyan Yang +2
Unsupervised speech emotion recognition (SER) focuses on addressing the problem of data sparsity and annotation bias of emotional speech. Reinforcement learning (RL) is a promising…
DisCo-Speech: Controllable Zero-Shot Speech Generation with A Disentangled Speech Codec
Tao Li, Wenshuo Ge, Zhichao Wang +6
Codec-based language models (LMs) have revolutionized text-to-speech (TTS). However, standard codecs entangle timbre and prosody, which hinders independent control in continuation-…
Teaching Audio Models to Reason: A Unified Framework for Source- and Layer-wise Distillation
Runyan Yang, Yuke Si, Yingying Gao +3
While large audio language models excel at tasks like ASR and emotion recognition, they still struggle with complex reasoning due to the modality gap between audio and text as well…
HarmoniFuse: A Component-Selective and Prompt-Adaptive Framework for Multi-Task Speech Language Modeling
Yuke Si, Runyan Yang, Yingying Gao +3
Recent advances in large language models have facilitated the development of unified speech language models (SLMs) capable of supporting multiple speech tasks within a shared archi…
DeCodec: Rethinking Audio Codecs as Universal Disentangled Representation Learners
Xiaoxue Luo, Jinwei Huang, Runyan Yang +4
Universal audio codecs learn entangled representations across audio types, whereas some specific codecs offer decoupled representations but are limited to speech. Real-world audio,…
DiffStyleTTS: Diffusion-based Hierarchical Prosody Modeling for Text-to-Speech with Diverse and Controllable Styles
Jiaxuan Liu, Zhaoci Liu, Yajun Hu +3
Human speech exhibits rich and flexible prosodic variations. To address the one-to-many mapping problem from text to prosody in a reasonable and flexible manner, we propose DiffSty…
VoxBlink2: A 100K+ Speaker Recognition Corpus and the Open-Set Speaker-Identification Benchmark
Yuke Lin, Ming Cheng, Fulin Zhang +3
In this paper, we provide a large audio-visual speaker recognition dataset, VoxBlink2, which includes approximately 10M utterances with videos from 110K+ speakers in the wild. This…
Exploring Energy-Based Models for Out-of-Distribution Detection in Dialect Identification
Yaqian Hao, Chenguang Hu, Yingying Gao +2
The diverse nature of dialects presents challenges for models trained on specific linguistic patterns, rendering them susceptible to errors when confronted with unseen or out-of-di…
On Calibration of Speech Classification Models: Insights from Energy-Based Model Investigations
Yaqian Hao, Chenguang Hu, Yingying Gao +2
For speech classification tasks, deep learning models often achieve high accuracy but exhibit shortcomings in calibration, manifesting as classifiers exhibiting overconfidence. The…
GenDistiller: Distilling Pre-trained Language Models based on an Autoregressive Generative Model
Yingying Gao, Shilei Zhang, Chao Deng +1
Pre-trained speech language models such as HuBERT and WavLM leverage unlabeled speech data for self-supervised learning and offer powerful representations for numerous downstream t…
CEC: A Noisy Label Detection Method for Speaker Recognition
Yao Shen, Yingying Gao, Yaqian Hao +4
Noisy labels are inevitable, even in well-annotated datasets. The detection of noisy labels is of significant importance to enhance the robustness of speaker recognition models. In…
PolySpeech: Exploring Unified Multitask Speech Models for Competitiveness with Single-task Models
Runyan Yang, Huibao Yang, Xiqing Zhang +6
Recently, there have been attempts to integrate various speech processing tasks into a unified model. However, few previous works directly demonstrated that joint optimization of d…
Plugin Speech Enhancement: A Universal Speech Enhancement Framework Inspired by Dynamic Neural Network
Yanan Chen, Zihao Cui, Yingying Gao +3
The expectation to deploy a universal neural network for speech enhancement, with the aim of improving noise robustness across diverse speech processing tasks, faces challenges due…
Cascaded Multi-task Adaptive Learning Based on Neural Architecture Search
Yingying Gao, Shilei Zhang, Zihao Cui +2
Cascading multiple pre-trained models is an effective way to compose an end-to-end system. However, fine-tuning the full cascaded model is parameter and memory inefficient and our…
GenDistiller: Distilling Pre-trained Language Models based on Generative Models
Yingying Gao, Shilei Zhang, Zihao Cui +3
Self-supervised pre-trained models such as HuBERT and WavLM leverage unlabeled speech data for representation learning and offer significantly improve for numerous downstream tasks…
MFSN: Multi-perspective Fusion Search Network For Pre-training Knowledge in Speech Emotion Recognition
Haiyang Sun, Fulin Zhang, Yingying Gao +3
Speech Emotion Recognition (SER) is an important research topic in human-computer interaction. Many recent works focus on directly extracting emotional cues through pre-trained kno…
VE-KWS: Visual Modality Enhanced End-to-End Keyword Spotting
Ao Zhang, He Wang, Pengcheng Guo +5
The performance of the keyword spotting (KWS) system based on audio modality, commonly measured in false alarms and false rejects, degrades significantly under the far field and no…
Meta Auxiliary Learning for Low-resource Spoken Language Understanding
Yingying Gao, Junlan Feng, Chao Deng +1
Spoken language understanding (SLU) treats automatic speech recognition (ASR) and natural language understanding (NLU) as a unified task and usually suffers from data scarcity. We…
A CTC Triggered Siamese Network with Spatial-Temporal Dropout for Speech Recognition
Yingying Gao, Junlan Feng, Tianrui Wang +2
Siamese networks have shown effective results in unsupervised visual representation learning. These models are designed to learn an invariant representation of two augmentations fo…
Multiple Confidence Gates For Joint Training Of SE And ASR
Tianrui Wang, Weibin Zhu, Yingying Gao +2
Joint training of speech enhancement model (SE) and speech recognition model (ASR) is a common solution for robust ASR in noisy environments. SE focuses on improving the auditory q…
Harmonic gated compensation network plus for ICASSP 2022 DNS CHALLENGE
Tianrui Wang, Weibin Zhu, Yingying Gao +3
The harmonic structure of speech is resistant to noise, but the harmonics may still be partially masked by noise. Therefore, we previously proposed a harmonic gated compensation ne…
HGCN: Harmonic gated compensation network for speech enhancement
Tianrui Wang, Weibin Zhu, Yingying Gao +2
Mask processing in the time-frequency (T-F) domain through the neural network has been one of the mainstreams for single-channel speech enhancement. However, it is hard for most mo…
Boundary and Context Aware Training for CIF-based Non-Autoregressive End-to-end ASR
Fan Yu, Haoneng Luo, Pengcheng Guo +6
Continuous integrate-and-fire (CIF) based models, which use a soft and monotonic alignment mechanism, have been well applied in non-autoregressive (NAR) speech recognition with com…