https://github.com/yluo42/TAC
FaSNet: Low-latency Adaptive Beamforming for Multi-microphone Audio Processing
Papers with Code 아카이브
Speech Recognition
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Speech Recognition is the task of converting spoken language into text. It involves recognizing the words spoken in an audio recording and transcribing them into a written format. The goal is to accurately transcribe the speech in real-time or from recorded audio, taking into account factors such as accents, speaking speed, and background noise.
<span style="color:grey; opacity: 0.6">( Image credit: SpecAugment )</span>
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/yoshifumi-nakano/visual-text-to-speech
FastSpeech 2: Fast and High-Quality End-to-End Text to Speech
https://github.com/yoshitomo-matsubara/bottlefit-split_computing
Split Computing and Early Exiting for Deep Learning Applications: Survey and Research Challenges
https://github.com/yoshitomo-matsubara/head-network-distillation
Split Computing and Early Exiting for Deep Learning Applications: Survey and Research Challenges
https://github.com/yoshitomo-matsubara/hnd-ghnd-object-detectors
Split Computing and Early Exiting for Deep Learning Applications: Survey and Research Challenges
https://github.com/yoshitomo-matsubara/sc2-benchmark
Split Computing and Early Exiting for Deep Learning Applications: Survey and Research Challenges
https://github.com/yoshitomo-matsubara/supervised-compression
Split Computing and Early Exiting for Deep Learning Applications: Survey and Research Challenges
https://github.com/yoshitomo-matsubara/torchdistill
https://github.com/yrhvivian/pytorch-kaldi
https://github.com/yuchen005/unified-enhance-separation
Interactive Feature Fusion for End-to-End Noise-Robust Speech Recognition
https://github.com/yuetan031/fedproto
Communication-Efficient Learning of Deep Networks from Decentralized Data
https://github.com/yusufsugiono/klasifikasi-gambar-bunga
https://github.com/yw0nam/DenseNet
https://github.com/yxlu-0102/MP-SENet
Source-Filter-Based Generative Adversarial Neural Vocoder for High Fidelity Speech Synthesis
https://github.com/yzyouzhang/AIR-ASVspoof
SAMO: Speaker Attractor Multi-Center One-Class Learning for Voice Anti-Spoofing
https://github.com/ze1gades/diary
SkinAugment: Auto-Encoding Speaker Conversions for Automatic Speech Translation
https://github.com/zechenli03/sensorllm
https://github.com/zhangbo2008/fastSpeeck2_chinese_train
FastSpeech 2: Fast and High-Quality End-to-End Text to Speech
https://github.com/zhangzibin/char-rnn-chinese
Scheduled Sampling for Sequence Prediction with Recurrent Neural Networks
https://github.com/zhenghuatan/audio-adversarial-examples
Speech Commands: A Dataset for Limited-Vocabulary Speech Recognition
https://github.com/zhihaozhang97/ru-ai
Text-Free Image-to-Speech Synthesis Using Learned Segmental Units
https://github.com/zhong110020/Tensorflow-TCN
https://github.com/zhong110020/keras-tcn
https://github.com/zhuangdizhu/FedGen
Communication-Efficient Learning of Deep Networks from Decentralized Data
https://github.com/zhuzilin/ring-flash-attention
https://github.com/ziye2chen/LLMs-for-Mathematical-Analysis
https://github.com/zjZSTU/ResNet
https://github.com/zju-vipa/KamalEngine
Hearing Lips: Improving Lip Reading by Distilling Speech Recognizers
https://github.com/zjysteven/mixoe
A Baseline for Detecting Misclassified and Out-of-Distribution Examples in Neural Networks
https://github.com/zliucr/coach
https://github.com/zll1996/TCN
https://github.com/zziz/pwc
https://gitlab.com/Jaco-Assistant/deepspeech-polyglot
Scribosermo: Fast Speech-to-Text models for German and other Languages
https://gitlab.com/Jaco-Assistant/finstreder
EESEN: End-to-End Speech Recognition using Deep RNN Models and WFST-based Decoding
https://gitlab.com/birder/birder
https://gitlab.com/imahn/l2lflows
CaloFlow II: Even Faster and Still Accurate Generation of Calorimeter Showers with Normalizing Flows
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.