https://github.com/kohei0209/espnet
Reproducing Whisper-Style Training Using an Open-Source Toolkit and Publicly Available Data
Papers with Code 아카이브
Speech Recognition
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- 평가표
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- 보존된 평가 기록
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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/kooBH/VFWS
VoiceFilter: Targeted Voice Separation by Speaker-Conditioned Spectrogram Masking
https://github.com/krantirk/Wav2letterPlus
wav2letter++: The Fastest Open-source Speech Recognition System
https://github.com/krishnakarthi/COVID-19_Prediction
https://github.com/krishnap25/trfa
Communication-Efficient Learning of Deep Networks from Decentralized Data
https://github.com/kssteven418/Q-ASR
Integer-only Zero-shot Quantization for Efficient Speech Recognition
https://github.com/ksw0306/ClariNet
ClariNet: Parallel Wave Generation in End-to-End Text-to-Speech
https://github.com/kunato/mt3-pytorch
https://github.com/kunglab/ddnn
Split Computing and Early Exiting for Deep Learning Applications: Survey and Research Challenges
https://github.com/kylemin/SPELL
STHG: Spatial-Temporal Heterogeneous Graph Learning for Advanced Audio-Visual Diarization
https://github.com/kyutai-labs/hibiki
Moshi: a speech-text foundation model for real-time dialogue
https://github.com/kyutai-labs/moshivis
Moshi: a speech-text foundation model for real-time dialogue
https://github.com/lRomul/argus-freesound
SpecAugment: A Simple Data Augmentation Method for Automatic Speech Recognition
https://github.com/lab-midas/med_segmentation
https://github.com/lakahaga/dc-comix-tts
https://github.com/laleye/ALFFA_PUBLIC
https://github.com/lancopku/avg-avg
A Baseline for Detecting Misclassified and Out-of-Distribution Examples in Neural Networks
https://github.com/leandromineti/ml-curriculum
https://github.com/leandromineti/ml-knowledge-graph
https://github.com/leonty1/essm
Efficiently Modeling Long Sequences with Structured State Spaces
https://github.com/leonwlw/wenet
WeNet 2.0: More Productive End-to-End Speech Recognition Toolkit
https://github.com/levis0045/snips-nlu
https://github.com/lifeiteng/naturalspeech3_facodec
NaturalSpeech 3: Zero-Shot Speech Synthesis with Factorized Codec and Diffusion Models
https://github.com/lifeiteng/vall-e
Neural Codec Language Models are Zero-Shot Text to Speech Synthesizers
https://github.com/lifesailor/data-driven-predictive-maintenance
Deep Learning and Its Applications to Machine Health Monitoring: A Survey
https://github.com/liguigui/speech-to-text-wavenet
https://github.com/lilei-John/wav2letter
wav2letter++: The Fastest Open-source Speech Recognition System
https://github.com/lilianemomeni/KWS-Net
Zero-shot keyword spotting for visual speech recognition in-the-wild
https://github.com/limberc/deep-gradient-compression
Deep Gradient Compression: Reducing the Communication Bandwidth for Distributed Training
https://github.com/lin9x/av-sepformer
Muse: Multi-modal target speaker extraction with visual cues
https://github.com/lionelmessi6410/ntga
https://github.com/lissyx/STT
https://github.com/liusongxiang/ppg-vc
Any-to-Many Voice Conversion with Location-Relative Sequence-to-Sequence Modeling
https://github.com/liutianlin0121/seislm
wav2vec 2.0: A Framework for Self-Supervised Learning of Speech Representations
https://github.com/liuzhuang13/DenseNetCaffe
https://github.com/liyaSileshi/amharic-sentiment-analysis
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.