https://github.com/viig99/mixmatch-freesound
SpecAugment: A Simple Data Augmentation Method for Automatic Speech Recognition
Papers with Code 아카이브
Automatic Speech Recognition (ASR)
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Automatic Speech Recognition (ASR) involves converting spoken language into written text. It is designed to transcribe spoken words into text in real-time, allowing people to communicate with computers, mobile devices, and other technology using their voice. The goal of Automatic Speech Recognition is to accurately transcribe speech, taking into account variations in accent, pronunciation, and speaking style, as well as background noise and other factors that can affect speech quality.
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/vishKurama/audio-adversarial-attack
Audio Adversarial Examples: Targeted Attacks on Speech-to-Text
https://github.com/wd929/NeMo
https://github.com/wenet-e2e/wenet
Conformer: Convolution-augmented Transformer for Speech Recognition
https://github.com/wenet-e2e/west
An Embarrassingly Simple Approach for LLM with Strong ASR Capacity
https://github.com/widzemin/audio_project
Speech Commands: A Dataset for Limited-Vocabulary Speech Recognition
https://github.com/wnhsu/FactorizedHierarchicalVAE
Unsupervised Learning of Disentangled and Interpretable Representations from Sequential Data
https://github.com/wnhsu/ScalableFHVAE
Unsupervised Learning of Disentangled and Interpretable Representations from Sequential Data
https://github.com/x-lance/kwstreamingsearch
Streaming Keyword Spotting Boosted by Cross-layer Discrimination Consistency
https://github.com/yangyucheng000/University/tree/main/model-2/hubert
HuBERT-EE: Early Exiting HuBERT for Efficient Speech Recognition
https://github.com/yangyucheng000/University/tree/main/model-3/speech_encoder_decoder
https://github.com/yangyucheng000/University/tree/main/model-3/speecht5
SpeechT5: Unified-Modal Encoder-Decoder Pre-Training for Spoken Language Processing
https://github.com/yuchen005/unified-enhance-separation
Interactive Feature Fusion for End-to-End Noise-Robust Speech Recognition
https://github.com/ze1gades/diary
SkinAugment: Auto-Encoding Speaker Conversions for Automatic Speech Translation
https://github.com/zhenghuatan/audio-adversarial-examples
Speech Commands: A Dataset for Limited-Vocabulary Speech Recognition
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/zziz/pwc
https://gitlab.com/Jaco-Assistant/finstreder
EESEN: End-to-End Speech Recognition using Deep RNN Models and WFST-based Decoding
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.