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Speech Recognition

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하위 태스크: 11
평가표: 236
보존된 평가 기록: 398

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/2023-MindSpore-4/Code14/tree/main/resnet3d

The NPU-ASLP-LiAuto System Description for Visual Speech Recognition in CNVSRC 2023

https://github.com/2023-MindSpore-4/Code8/tree/main/crnn_seq2seq_ocr

The Sequence-to-Sequence Baseline for the Voice Conversion Challenge 2020: Cascading ASR and TTS

https://github.com/2024-MindSpore-1/Code2/tree/main/model-1/bert_japanese

HuBERT: Self-Supervised Speech Representation Learning by Masked Prediction of Hidden Units

https://github.com/2024-MindSpore-1/Code2/tree/main/model-1/data2vec

data2vec: A General Framework for Self-supervised Learning in Speech, Vision and Language

https://github.com/2024-MindSpore-1/Code2/tree/main/model-1/fastspeech2_conformer

FastSpeech 2: Fast and High-Quality End-to-End Text to Speech

https://github.com/2024-MindSpore-1/Code6/tree/main/3D_DenseNet

Densely Connected Convolutional Networks

https://github.com/2024-MindSpore-1/Code7/tree/main/conformer

Conformer-based Target-Speaker Automatic Speech Recognition for Single-Channel Audio

https://github.com/2noise/chattts

Neural Codec Language Models are Zero-Shot Text to Speech Synthesizers

https://github.com/2sang/OOD-baseline

A Baseline for Detecting Misclassified and Out-of-Distribution Examples in Neural Networks

https://github.com/30stomercury/Automatic_Speech_Recognition

Attention-Based Models for Speech Recognition

https://github.com/3outeille/DSD-TF2

DSD: Dense-Sparse-Dense Training for Deep Neural Networks

https://github.com/3outeille/DSD-training

DSD: Dense-Sparse-Dense Training for Deep Neural Networks

https://github.com/592595/TERA

TERA: Self-Supervised Learning of Transformer Encoder Representation for Speech

https://github.com/9552nZ/SmartSheetMusic

An End-to-End Neural Network for Polyphonic Piano Music Transcription

https://github.com/AFAgarap/cnn-svm

Deep Learning using Linear Support Vector Machines

https://github.com/AFAgarap/malware-classification

Deep Learning using Linear Support Vector Machines

https://github.com/AFAgarap/wisconsin-breast-cancer

A Neural Network Architecture Combining Gated Recurrent Unit (GRU) and Support Vector Machine (SVM) for Intrusion Detection in Network Traffic Data

https://github.com/AI-Huang/WaveNet

WaveNet: A Generative Model for Raw Audio

https://github.com/AIdeaLab/wav2vec2_docker

wav2vec 2.0: A Framework for Self-Supervised Learning of Speech Representations

https://github.com/ANLGBOY/WaveNODE

WaveNODE: A Continuous Normalizing Flow for Speech Synthesis

https://github.com/Abdallah-Hesham99/tell_your_motor_speed

Speech Commands: A Dataset for Limited-Vocabulary Speech Recognition

https://github.com/Abdulk084/Chemception

Chemception: A Deep Neural Network with Minimal Chemistry Knowledge Matches the Performance of Expert-developed QSAR/QSPR Models

https://github.com/AirBernard/DenseNet-by-Pytorch

Densely Connected Convolutional Networks

https://github.com/Alexander-H-Liu/NPC

Generative Pre-Training for Speech with Autoregressive Predictive Coding

https://github.com/Alpe6825/Unicornn

Speech Commands: A Dataset for Limited-Vocabulary Speech Recognition

https://github.com/Amharic-STT/STT-engine

OkwuGbé: End-to-End Speech Recognition for Fon and Igbo

https://github.com/AmirmohammadRostami/ASV-anti-spoofing-with-EABN

EfficientNet-Absolute Zero for Continuous Speech Keyword Spotting

https://github.com/AnReu/T5-lenses

DecoderLens: Layerwise Interpretation of Encoder-Decoder Transformers

https://github.com/Anil1331/DenseNet

Densely Connected Convolutional Networks

https://github.com/Anustup900/Tensorflow-Speech-Recognition

Very Deep Convolutional Neural Networks for Robust Speech Recognition

https://github.com/ApexPredator1/DenseNet_tensorflow

Densely Connected Convolutional Networks

https://github.com/ArashRahnama/Adversarial-Explainations-for-Artificial-Intelligence-systems-AXAI

An Adversarial Approach for Explaining the Predictions of Deep Neural Networks

https://github.com/ArashRahnama/Adversarial-Explanations-for-Artificial-Intelligence-Systems-AXAI

An Adversarial Approach for Explaining the Predictions of Deep Neural Networks

https://github.com/Arizona-Voice/Arizona-spotting

wav2vec 2.0: A Framework for Self-Supervised Learning of Speech Representations

https://github.com/AryanShekarlaban/data2vec-pytorch

data2vec: A General Framework for Self-supervised Learning in Speech, Vision and Language

https://github.com/AshwinDeshpande96/Hierarchical-Softmax

Strategies for Training Large Vocabulary Neural Language Models

출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.