https://github.com/diggerdu/AudioMamba
Speech Commands: A Dataset for Limited-Vocabulary Speech Recognition
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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/diggerdu/audiorwkv
Speech Commands: A Dataset for Limited-Vocabulary Speech Recognition
https://github.com/dreamtheater123/voxeval
https://github.com/drumpt/RotNet-OOD
A Baseline for Detecting Misclassified and Out-of-Distribution Examples in Neural Networks
https://github.com/ebouteillon/freesound-audio-tagging-2019
SpecAugment: A Simple Data Augmentation Method for Automatic Speech Recognition
https://github.com/ecnu-cross-innovation-lab/ent
Factorized Neural Transducer for Efficient Language Model Adaptation
https://github.com/etapiahe/adversarial_audio_attack
Audio Adversarial Examples: Targeted Attacks on Speech-to-Text
https://github.com/exgc/avmust-ted
https://github.com/facebookresearch/covost
https://github.com/facebookresearch/voxpopuli
https://github.com/ferugit/iterative-pseudo-forced-alignment-ctc
Iterative pseudo-forced alignment by acoustic CTC loss for self-supervised ASR domain adaptation
https://github.com/fracorti/reds
Speech Commands: A Dataset for Limited-Vocabulary Speech Recognition
https://github.com/freds0/data_augmentation_for_asr
SpecAugment: A Simple Data Augmentation Method for Automatic Speech Recognition
https://github.com/freds0/kabooks
Pansori: ASR Corpus Generation from Open Online Video Contents
https://github.com/freds0/katube
Pansori: ASR Corpus Generation from Open Online Video Contents
https://github.com/gentaiscool/end2end-asr-pytorch
Syllable-Based Sequence-to-Sequence Speech Recognition with the Transformer in Mandarin Chinese
https://github.com/georgesterpu/avsr-tf1
Attention-based Audio-Visual Fusion for Robust Automatic Speech Recognition
https://github.com/gonenhila/codeswitching-lm
https://github.com/google-research/leaf-audio
SpecAugment: A Simple Data Augmentation Method for Automatic Speech Recognition
https://github.com/google/aqt
4-bit Conformer with Native Quantization Aware Training for Speech Recognition
https://github.com/guyAmit/GLOD
A Baseline for Detecting Misclassified and Out-of-Distribution Examples in Neural Networks
https://github.com/hasangchun/ContextNet
https://github.com/hgstudent/las
SpecAugment: A Simple Data Augmentation Method for Automatic Speech Recognition
https://github.com/hhhaaahhhaa/asr-tta
Continual Test-time Adaptation for End-to-end Speech Recognition on Noisy Speech
https://github.com/huckiyang/QuantumSpeech-QCNN
https://github.com/huggingface/datasets
TED-LIUM 3: twice as much data and corpus repartition for experiments on speaker adaptation
https://github.com/huggingface/open_asr_leaderboard
ESB: A Benchmark For Multi-Domain End-to-End Speech Recognition
https://github.com/huggingface/transformers
SpeechT5: Unified-Modal Encoder-Decoder Pre-Training for Spoken Language Processing
https://github.com/huutuongtu/skd-ctc
Guiding Frame-Level CTC Alignments Using Self-knowledge Distillation
https://github.com/idiap/sparch
Speech Commands: A Dataset for Limited-Vocabulary Speech Recognition
https://github.com/ishandutta2007/Speech-Denoising-Landscape
Single-Channel Multi-Speaker Separation using Deep Clustering
https://github.com/iver56/audiomentations
SpecAugment: A Simple Data Augmentation Method for Automatic Speech Recognition
https://github.com/jackjhliu/End-to-End-Mandarin-ASR
SpecAugment: A Simple Data Augmentation Method for Automatic Speech Recognition
https://github.com/jaketae/conformer
Conformer: Convolution-augmented Transformer for Speech Recognition
https://github.com/jarfo/gcommands
Speech Commands: A Dataset for Limited-Vocabulary Speech Recognition
https://github.com/jasonppy/promptingwhisper
How2: A Large-scale Dataset for Multimodal Language Understanding
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.