https://github.com/skhu101/tdnn-f_nas
공식 코드Neural Architecture Search For LF-MMI Trained Time Delay Neural Networks
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/skit-ai/speech-to-intent-dataset
공식 코드https://github.com/slp-rl/sc-phase
공식 코드A Systematic Comparison of Phonetic Aware Techniques for Speech Enhancement
https://github.com/smileslab/comparative-analysis-voice-spoofing
공식 코드https://github.com/snipsco/nlu-benchmark
공식 코드https://github.com/snipsco/snips-nlu
공식 코드https://github.com/softsys4ai/FlexiBO
공식 코드FlexiBO: A Decoupled Cost-Aware Multi-Objective Optimization Approach for Deep Neural Networks
https://github.com/sohamtiwari3120/yoho-on-voice
공식 코드Evaluating robustness of You Only Hear Once(YOHO) Algorithm on noisy audios in the VOICe Dataset
https://github.com/sony/bigvsan
공식 코드BigVSAN: Enhancing GAN-based Neural Vocoders with Slicing Adversarial Network
https://github.com/sony/bigvsan_eval
공식 코드BigVSAN: Enhancing GAN-based Neural Vocoders with Slicing Adversarial Network
https://github.com/sooftware/KoSpeech
공식 코드KoSpeech: Open-Source Toolkit for End-to-End Korean Speech Recognition
https://github.com/soroushmehr/sampleRNN_ICLR2017
공식 코드SampleRNN: An Unconditional End-to-End Neural Audio Generation Model
https://github.com/sp-nitech/diffsptk
공식 코드Embedding a Differentiable Mel-cepstral Synthesis Filter to a Neural Speech Synthesis System
https://github.com/spaghettiSystems/serval
공식 코드SER Evals: In-domain and Out-of-domain Benchmarking for Speech Emotion Recognition
https://github.com/sparkssss/aequevox
공식 코드AequeVox: Automated Fairness Testing of Speech Recognition Systems
https://github.com/speech-lab-iitm/ccc-wav2vec-2.0
공식 코드https://github.com/speech-lab-iitm/data2vec-aqc
공식 코드data2vec-aqc: Search for the right Teaching Assistant in the Teacher-Student training setup
https://github.com/speechLabBcCuny/onssen
공식 코드Onssen: an open-source speech separation and enhancement library
https://github.com/speechbrain/benchmarks
공식 코드CL-MASR: A Continual Learning Benchmark for Multilingual ASR
https://github.com/speechbrain/speechbrain
공식 코드SoundChoice: Grapheme-to-Phoneme Models with Semantic Disambiguation
https://github.com/speechcolab/leaderboard
공식 코드SpeechColab Leaderboard: An Open-Source Platform for Automatic Speech Recognition Evaluation
https://github.com/spkgyk/RTFS-Net
공식 코드RTFS-Net: Recurrent Time-Frequency Modelling for Efficient Audio-Visual Speech Separation
https://github.com/spkgyk/TDFNet
공식 코드TDFNet: An Efficient Audio-Visual Speech Separation Model with Top-down Fusion
https://github.com/springhuo/mavd
공식 코드MAVD: The First Open Large-Scale Mandarin Audio-Visual Dataset with Depth Information
https://github.com/sreyan88/lipger
공식 코드LipGER: Visually-Conditioned Generative Error Correction for Robust Automatic Speech Recognition
https://github.com/srijith-rkr/whispering-llama
공식 코드Whispering LLaMA: A Cross-Modal Generative Error Correction Framework for Speech Recognition
https://github.com/srvk/how2-dataset
공식 코드How2: A Large-scale Dataset for Multimodal Language Understanding
https://github.com/ssmlkl/mntts2
공식 코드MnTTS2: An Open-Source Multi-Speaker Mongolian Text-to-Speech Synthesis Dataset
https://github.com/state-spaces/s4
공식 코드Efficiently Modeling Long Sequences with Structured State Spaces
https://github.com/stefbraun/rnn_benchmarks
공식 코드https://github.com/stellali7/ssl_psr
공식 코드A Quantitative Approach to Understand Self-Supervised Models as Cross-lingual Feature Extractors
https://github.com/steventan0110/star
공식 코드https://github.com/stevenvdeeckt/cgn_cl_dialect
공식 코드Continual Learning for Monolingual End-to-End Automatic Speech Recognition
https://github.com/stevenvdeeckt/online-cl-for-asr
공식 코드Rehearsal-Free Online Continual Learning for Automatic Speech Recognition
https://github.com/stevenvdeeckt/unsupervised-ocl-for-asr
공식 코드Unsupervised Online Continual Learning for Automatic Speech Recognition
https://github.com/stt4sg/dialektsammlung-public
공식 코드SDS-200: A Swiss German Speech to Standard German Text Corpus
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.