https://github.com/HLasse/wav2vec_finetune
SpecAugment: A Simple Data Augmentation Method for Automatic Speech Recognition
Papers with Code 아카이브
Speech Recognition
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
- 하위 태스크
- 11
- 평가표
- 236
- 보존된 평가 기록
- 398
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/HLinShan/vision_networks
https://github.com/HaiFengZeng/clari_wavenet_vocoder
https://github.com/HarunoriKawano/BEST-RQ
Self-supervised Learning with Random-projection Quantizer for Speech Recognition
https://github.com/HarunoriKawano/Conformer
Conformer: Convolution-augmented Transformer for Speech Recognition
https://github.com/HarunoriKawano/Wav2vec2.0
wav2vec 2.0: A Framework for Self-Supervised Learning of Speech Representations
https://github.com/Hashir44/muraxray
https://github.com/HawkAaron/warp-transducer
https://github.com/HazyResearch/metal
https://github.com/HeapHop30/graph-attention-nets
Geometric deep learning on graphs and manifolds using mixture model CNNs
https://github.com/HeleneFabia/keyword-spotter
SpecAugment: A Simple Data Augmentation Method for Automatic Speech Recognition
https://github.com/HeliosX7/voice-filter
VoiceFilter: Targeted Voice Separation by Speaker-Conditioned Spectrogram Masking
https://github.com/HongshengHu/SIAs-Beyond_MIAs_in_Federated_Learning
Communication-Efficient Learning of Deep Networks from Decentralized Data
https://github.com/HsiehKang/wavenet/blob/main/wavenet.ipynb
https://github.com/Hypotheses-Paradise/UADF
https://github.com/IAHispano/Applio
HiFi-GAN: Generative Adversarial Networks for Efficient and High Fidelity Speech Synthesis
https://github.com/IAHispano/Applio/tree/exp/vocoders/rvc/lib/algorithm
BigVGAN: A Universal Neural Vocoder with Large-Scale Training
https://github.com/IBM/MAX-Speech-to-Text-Converter
https://github.com/IBM/ostl
https://github.com/ID56/Torch-KWT
Keyword Transformer: A Self-Attention Model for Keyword Spotting
https://github.com/IGITUGraz/LSNN-official
Long short-term memory and learning-to-learn in networks of spiking neurons
https://github.com/IMDxD/NonAttentiveTacotron
https://github.com/IMvision12/keras-vision-models
https://github.com/IPINGCHOU/NTU_MachineLearning
Scheduled Sampling for Sequence Prediction with Recurrent Neural Networks
https://github.com/IvKosar/text2speech
https://github.com/JJoving/SMLAT
https://github.com/JTan2231/DenseNet
https://github.com/JackSyu/AE-MSR
https://github.com/JakobCode/UncertaintyInNeuralNetworks_Resources
A Baseline for Detecting Misclassified and Out-of-Distribution Examples in Neural Networks
https://github.com/Jeevesh8/Cross-Lingual-Voice-Cloning
Natural TTS Synthesis by Conditioning WaveNet on Mel Spectrogram Predictions
https://github.com/JeongHun0716/e-mvsr
https://github.com/JetRunner/PABEE
Split Computing and Early Exiting for Deep Learning Applications: Survey and Research Challenges
https://github.com/JoegameZhou/MindSpeech
Unsupervised Cross-lingual Representation Learning for Speech Recognition
https://github.com/Joshuaoneheart/Fintech-Final-Report
Conformer: Convolution-augmented Transformer for Speech Recognition
https://github.com/JoungheeKim/Non-Attentive-Tacotron
wav2vec 2.0: A Framework for Self-Supervised Learning of Speech Representations
https://github.com/JuliusKunze/speechless
Wav2Letter: an End-to-End ConvNet-based Speech Recognition System
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.