Papers with Code 아카이브
Speech Recognition
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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/gal-dmitry/INTERRUPTION_DETECTION_PUBLIC
Text-Based Detection of On-Hold Scripts in Contact Center Calls
https://github.com/galaxycong/hpmdubbing
FastSpeech 2: Fast and High-Quality End-to-End Text to Speech
https://github.com/galv/lingvo-copy
Lingvo: a Modular and Scalable Framework for Sequence-to-Sequence Modeling
https://github.com/gargarchit/60DaysOfUdacity
https://github.com/gargimahale/Speech-Recognition-Using-Tensorflow
https://github.com/gcambara/cape
CAPE: Encoding Relative Positions with Continuous Augmented Positional Embeddings
https://github.com/gcambara/wav2letter
wav2letter++: The Fastest Open-source Speech Recognition System
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/ggerganov/whisper.cpp
https://github.com/giampierosalvi/AffordancesAndSpeech
Language Bootstrapping: Learning Word Meanings From Perception-Action Association
https://github.com/gladisor/TextGenerator
https://github.com/glakshay/Generating-audio-DL
https://github.com/gmum/Zero-Time-Waste
Split Computing and Early Exiting for Deep Learning Applications: Survey and Research Challenges
https://github.com/gonenhila/codeswitching-lm
https://github.com/google-research/last
Global Normalization for Streaming Speech Recognition in a Modular Framework
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/google/fedjax
Communication-Efficient Learning of Deep Networks from Decentralized Data
https://github.com/google/lyra
https://github.com/grammatek/iceprondict
https://github.com/greatsharma/DeepLearning-Papers-Implementation
https://github.com/gteu/reaptime-ppg-vc
https://github.com/gtn-org/gtn
https://github.com/guyAmit/GLOD
A Baseline for Detecting Misclassified and Out-of-Distribution Examples in Neural Networks
https://github.com/hadi-gharibi/pytorch-lstm
https://github.com/hasangchun/ContextNet
https://github.com/hasangchun/Transformer-Transducer
https://github.com/hash2430/pitchtron
Style Tokens: Unsupervised Style Modeling, Control and Transfer in End-to-End Speech Synthesis
https://github.com/hbahadirsahin/text_categorization
https://github.com/hcy71o/autovocoder
https://github.com/heatz123/naturalspeech
NaturalSpeech: End-to-End Text to Speech Synthesis with Human-Level Quality
https://github.com/hgstudent/las
https://github.com/hgupta01/svm_classification_keras
https://github.com/hhguo/msmc-tts
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.