https://github.com/tarepan/jsss
JSSS: free Japanese speech corpus for summarization and simplification
Papers with Code 아카이브
Speech Recognition
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- 평가표
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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/tarepan/jsut
JSUT corpus: free large-scale Japanese speech corpus for end-to-end speech synthesis
https://github.com/tartunlp/transformertts
https://github.com/taylor-914/DenseNet
https://github.com/tensorflow/models/tree/master/research/deep_speech
Deep Speech 2: End-to-End Speech Recognition in English and Mandarin
https://github.com/text-to-audio/make-an-audio
ProDiff: Progressive Fast Diffusion Model For High-Quality Text-to-Speech
https://github.com/theamrzaki/text_summurization_abstractive_methods
Scheduled Sampling for Sequence Prediction with Recurrent Neural Networks
https://github.com/thejungwon/gc-fed
Communication-Efficient Learning of Deep Networks from Decentralized Data
https://github.com/thepowerfuldeez/tacotron2
Natural TTS Synthesis by Conditioning WaveNet on Mel Spectrogram Predictions
https://github.com/theswgong/MoNet
Geometric deep learning on graphs and manifolds using mixture model CNNs
https://github.com/thethirdwheel/malumagraph
https://github.com/thorwhalen/sla
https://github.com/thorwhalen/slang
https://github.com/thuhcsi/tacotron
https://github.com/thuiar/textoir
A Baseline for Detecting Misclassified and Out-of-Distribution Examples in Neural Networks
https://github.com/thuiar/textoir-demo
A Baseline for Detecting Misclassified and Out-of-Distribution Examples in Neural Networks
https://github.com/thuspmi/cat
https://github.com/tigthor/Voice-Cloning-AI
https://github.com/titu1994/DenseNet
https://github.com/tmatha/lstm
https://github.com/tom-doerr/audio_adversarial_examples
Audio Adversarial Examples: Targeted Attacks on Speech-to-Text
https://github.com/tommytracey/aind-capstone
Residual LSTM: Design of a Deep Recurrent Architecture for Distant Speech Recognition
https://github.com/tomsercu/lstm
https://github.com/tonyyouyou/mamba-in-speech
https://github.com/toopster/dsc-capstone-project
Speech Commands: A Dataset for Limited-Vocabulary Speech Recognition
https://github.com/tqch/esgd-ws
Evolutionary Stochastic Gradient Descent for Optimization of Deep Neural Networks
https://github.com/trevor-richardson/rnn_zoo
A Simple Way to Initialize Recurrent Networks of Rectified Linear Units
https://github.com/trinhtuanvubk/diff-vc
Diffusion-Based Voice Conversion with Fast Maximum Likelihood Sampling Scheme
https://github.com/trusthlt/dp-rewrite
https://github.com/tuanio/conformer-rnnt
Conformer: Convolution-augmented Transformer for Speech Recognition
https://github.com/tuanio/deepspeech-ctc
https://github.com/tuanio/nextformer
Conformer: Convolution-augmented Transformer for Speech Recognition
https://github.com/tuanio/noisy-student-training-asr
Pushing the Limits of Semi-Supervised Learning for Automatic Speech Recognition
https://github.com/tudarmstadt-lt/kaldi-tuda-de
https://github.com/ubc-nlp/udistilwhisper
To Distill or Not to Distill? On the Robustness of Robust Knowledge Distillation
https://github.com/ucsd-dsc-arts/dsc160-final-dsc160-final-group19
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.