https://github.com/oliverzhang42/ood_medical_images
A Baseline for Detecting Misclassified and Out-of-Distribution Examples in Neural Networks
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/openspeech-team/openspeech
https://github.com/pariajm/e2e-asr-and-disfluency-removal-evaluation
https://github.com/park-cheol/ASR-Conformer
SpecAugment: A Simple Data Augmentation Method for Automatic Speech Recognition
https://github.com/park-cheol/ASR-Transformer
https://github.com/pawan47/nilmtk_readings
Neural NILM: Deep Neural Networks Applied to Energy Disaggregation
https://github.com/payalmohapatra/Multimodal-Speech-Disfluency
https://github.com/phanxuanphucnd/Arizona-asr
Conformer: Convolution-augmented Transformer for Speech Recognition
https://github.com/phanxuanphucnd/conformer
Conformer: Convolution-augmented Transformer for Speech Recognition
https://github.com/phanxuanphucnd/wav2kws
Speech Commands: A Dataset for Limited-Vocabulary Speech Recognition
https://github.com/pragyak412/Improving-Voice-Separation-by-Incorporating-End-To-End-Speech-Recognition
Improving Voice Separation by Incorporating End-to-end Speech Recognition
https://github.com/pspratling/Speech-Recognition
Speech Commands: A Dataset for Limited-Vocabulary Speech Recognition
https://github.com/pulp-platform/eae-kws
Speech Commands: A Dataset for Limited-Vocabulary Speech Recognition
https://github.com/pwc-1/Paper-10/tree/main/speech_encoder_decoder
A Comparison of Techniques for Language Model Integration in Encoder-Decoder Speech Recognition
https://github.com/pwc-1/Paper-10/tree/main/speecht5
SpeechT5: Unified-Modal Encoder-Decoder Pre-Training for Spoken Language Processing
https://github.com/pwc-1/Paper-9/tree/main/3/stochastic-attention-head-removal-a-simple
https://github.com/pwc-1/Paper-9/tree/main/4/stochastic-attention-head-removal-a-simple
https://github.com/pwc-1/Paper-9/tree/main/5/wav2vec2_conformer
https://github.com/qute012/Wav2Keyword
Speech Commands: A Dataset for Limited-Vocabulary Speech Recognition
https://github.com/r9y9/icassp2020-espnet-tts-merlin-baseline
ESPnet-TTS: Unified, Reproducible, and Integratable Open Source End-to-End Text-to-Speech Toolkit
https://github.com/retrocirce/hts-audio-transformer
Speech Commands: A Dataset for Limited-Vocabulary Speech Recognition
https://github.com/rf5/simple-speech-commands
Speech Commands: A Dataset for Limited-Vocabulary Speech Recognition
https://github.com/rickyHong/OpenSeq2Seq-repl
Mixed-Precision Training for NLP and Speech Recognition with OpenSeq2Seq
https://github.com/robflynnyh/Self-Train-Before-You-Transcribe
Momentum Pseudo-Labeling for Semi-Supervised Speech Recognition
https://github.com/robflynnyh/long-context-asr
ESB: A Benchmark For Multi-Domain End-to-End Speech Recognition
https://github.com/roudimit/AVLnet
AVLnet: Learning Audio-Visual Language Representations from Instructional Videos
https://github.com/rufaelfekadu/seq2seq-vc
Pretraining Techniques for Sequence-to-Sequence Voice Conversion
https://github.com/rvoleti89/icaasp-2019-word-subs
Investigating the Effects of Word Substitution Errors on Sentence Embeddings
https://github.com/rwth-i6/returnn
RWTH ASR Systems for LibriSpeech: Hybrid vs Attention -- w/o Data Augmentation
https://github.com/rwth-i6/returnn-experiments/tree/master/2019-librispeech-system
RWTH ASR Systems for LibriSpeech: Hybrid vs Attention -- w/o Data Augmentation
https://github.com/s3prl/End-to-end-ASR-Pytorch
https://github.com/sadhusamik/fdlp_spectrogram
Radically Old Way of Computing Spectra: Applications in End-to-End ASR
https://github.com/salesforce/DAPC
Representation Learning for Sequence Data with Deep Autoencoding Predictive Components
https://github.com/sankalp2610/Speech_Command_Recognition
Speech Commands: A Dataset for Limited-Vocabulary Speech Recognition
https://github.com/saraalemadi/DroneAudioDataset
Speech Commands: A Dataset for Limited-Vocabulary Speech Recognition
https://github.com/sdrobert/more-or-let
Towards End-to-End Speech Recognition with Deep Convolutional Neural Networks
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.