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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/IS2AI/Kazakh_TTS

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KazakhTTS: An Open-Source Kazakh Text-to-Speech Synthesis Dataset

https://github.com/IS2AI/MultilingualASR

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A Study of Multilingual End-to-End Speech Recognition for Kazakh, Russian, and English

https://github.com/IS2AI/SpeakingFaces

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SpeakingFaces: A Large-Scale Multimodal Dataset of Voice Commands with Visual and Thermal Video Streams

https://github.com/IS2AI/Uzbek_ASR

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USC: An Open-Source Uzbek Speech Corpus and Initial Speech Recognition Experiments

https://github.com/ISmallFish/Libri-adhoc40

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Libri-adhoc40: A dataset collected from synchronized ad-hoc microphone arrays

https://github.com/JackKelly/neuralnilm_prototype

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Neural NILM: Deep Neural Networks Applied to Energy Disaggregation

https://github.com/JackSyu/Discriminative-Multi-modality-Speech-Recognition

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Discriminative Multi-modality Speech Recognition

https://github.com/JazminVidal/ssl-mispron

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Mispronunciation detection using self-supervised speech representations

https://github.com/JeongHun0716/MMS-LLaMA

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MMS-LLaMA: Efficient LLM-based Audio-Visual Speech Recognition with Minimal Multimodal Speech Tokens

https://github.com/JeongHun0716/zero-avsr

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Zero-AVSR: Zero-Shot Audio-Visual Speech Recognition with LLMs by Learning Language-Agnostic Speech Representations

https://github.com/Jiang-Yidi/TransformerDistillation-SLU

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Knowledge Distillation from BERT Transformer to Speech Transformer for Intent Classification

https://github.com/JunwenBai/DAPC

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Representation Learning for Sequence Data with Deep Autoencoding Predictive Components

https://github.com/KAIST-AILab/SyncVSR

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SyncVSR: Data-Efficient Visual Speech Recognition with End-to-End Crossmodal Audio Token Synchronization

https://github.com/KaiyangZhou/Dassl.pytorch

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Domain Generalization: A Survey

https://github.com/Kohei-Matsuura/Non-parallel-VC-on-Mboshi

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Generative Adversarial Training Data Adaptation for Very Low-resource Automatic Speech Recognition

https://github.com/KurdishBLARK/BD-4SK-ASR

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Kurdish (Sorani) Speech to Text: Presenting an Experimental Dataset

https://github.com/Kyubyong/g2p

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Learning pronunciation from a foreign language in speech synthesis networks

https://github.com/L0SG/NanoFlow

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NanoFlow: Scalable Normalizing Flows with Sublinear Parameter Complexity

https://github.com/LIAvignon/adversarial-disentangling-autoencoder-for-spk-representation

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Adversarial Disentanglement of Speaker Representation for Attribute-Driven Privacy Preservation

https://github.com/Lancer555/NICE

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NICE: Noise Injection and Clamping Estimation for Neural Network Quantization

https://github.com/LeonWlw/asr_blockformer

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Improving Mandarin Speech Recogntion with Block-augmented Transformer

https://github.com/Lhx94As/reducing_language_confusion

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Reducing Language confusion for Code-switching Speech Recognition with Token-level Language Diarization

https://github.com/LingweiMeng/Whisper-Sidecar

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Empowering Whisper as a Joint Multi-Talker and Target-Talker Speech Recognition System

https://github.com/MarkWuNLP/SemanticMask

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Semantic Mask for Transformer based End-to-End Speech Recognition

https://github.com/MaxSob/ASRNeuralClassification

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Hybrid phonetic-neural model for correction in speech recognition systems

https://github.com/MelissaChen15/control-vc

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ControlVC: Zero-Shot Voice Conversion with Time-Varying Controls on Pitch and Speed

https://github.com/Microsoft/EdgeML

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FastGRNN: A Fast, Accurate, Stable and Tiny Kilobyte Sized Gated Recurrent Neural Network

https://github.com/MingLunHan/CIF-PyTorch

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Knowledge Transfer from Pre-trained Language Models to Cif-based Speech Recognizers via Hierarchical Distillation

https://github.com/MingruiYuan/SpoofSV

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Spoofing Speaker Verification Systems with Deep Multi-speaker Text-to-speech Synthesis

https://github.com/MiuLab/Lattice-SLU

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Adapting Pretrained Transformer to Lattices for Spoken Language Understanding

https://github.com/NTRLab/MediaSpeech

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MediaSpeech: Multilanguage ASR Benchmark and Dataset

https://github.com/NVIDIA/NeMo

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Shallow Fusion of Weighted Finite-State Transducer and Language Model for Text Normalization

https://github.com/NVIDIA/NeMo/tree/main/nemo_text_processing/inverse_text_normalization

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NeMo Inverse Text Normalization: From Development To Production

https://github.com/NVIDIA/OpenSeq2Seq

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Mixed-Precision Training for NLP and Speech Recognition with OpenSeq2Seq

https://github.com/NVIDIA/flowtron

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Flowtron: an Autoregressive Flow-based Generative Network for Text-to-Speech Synthesis

https://github.com/NaoyukiKanda/LibriSpeechMix

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Minimum Bayes Risk Training for End-to-End Speaker-Attributed ASR

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