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/facebookresearch/voxpopuli
공식 코드https://github.com/facebookresearch/wav2letter/tree/master/recipes/ipl
공식 코드https://github.com/facebookresearch/wav2letter/tree/master/recipes/mls
공식 코드https://github.com/facebookresearch/wav2letter/tree/master/recipes/rasr
공식 코드https://github.com/fauxneticien/qbe-std_feats_eval
공식 코드https://github.com/fchest/m3anet
공식 코드M3ANet: Multi-scale and Multi-Modal Alignment Network for Brain-Assisted Target Speaker Extraction
https://github.com/fdschmidt93/fleurs-slu
공식 코드Fleurs-SLU: A Massively Multilingual Benchmark for Spoken Language Understanding
https://github.com/fengxin-bupt/Application-of-Word2vec-in-Phoneme-Recognition
공식 코드https://github.com/festivalhopper/swiss-parliaments-corpus-paper
공식 코드https://github.com/ffaisal93/sd-qa
공식 코드SD-QA: Spoken Dialectal Question Answering for the Real World
https://github.com/fgnt/meeteval
공식 코드https://github.com/fgnt/nara_wpe
공식 코드Acoustic modeling for Overlapping Speech Recognition: JHU Chime-5 Challenge System
https://github.com/fgnt/pb_chime5
공식 코드https://github.com/firdavsn/SurgicalFeedbackAI
공식 코드Automating Feedback Analysis in Surgical Training: Detection, Categorization, and Assessment
https://github.com/fireredteam/fireredasr
공식 코드https://github.com/fmfi-compbio/coral-basecaller
공식 코드https://github.com/formiel/fairseq
공식 코드Lightweight Adapter Tuning for Multilingual Speech Translation
https://github.com/formiel/fairseq/blob/master/examples/speech_to_text/docs/adapters.md
공식 코드Lightweight Adapter Tuning for Multilingual Speech Translation
https://github.com/formiel/speech-translation
공식 코드Dual-decoder Transformer for Joint Automatic Speech Recognition and Multilingual Speech Translation
https://github.com/francoisgrondin/steernet
공식 코드GEV Beamforming Supported by DOA-based Masks Generated on Pairs of Microphones
https://github.com/freewym/espresso
공식 코드Espresso: A Fast End-to-end Neural Speech Recognition Toolkit
https://github.com/funaudiollm/cosyvoice
공식 코드https://github.com/g-milis/NEUTART
공식 코드https://github.com/g8a9/multilingual-asr-gender-gap
공식 코드Twists, Humps, and Pebbles: Multilingual Speech Recognition Models Exhibit Gender Performance Gaps
https://github.com/gabrielmittag/NISQA
공식 코드Deep Learning Based Assessment of Synthetic Speech Naturalness
https://github.com/gal-dmitry/HOLD_DETECTION_PUBLIC
공식 코드Text-Based Detection of On-Hold Scripts in Contact Center Calls
https://github.com/gatech-eic/s3-router
공식 코드https://github.com/gauthelo/kallaama-speech-dataset
공식 코드https://github.com/gbegus/articulationgan
공식 코드Articulation GAN: Unsupervised modeling of articulatory learning
https://github.com/gemelo-ai/vocos
공식 코드https://github.com/gemengtju/l-spex
공식 코드https://github.com/gengxuelong/wenet_LLM_from_ASLP
공식 코드Unveiling the Potential of LLM-Based ASR on Chinese Open-Source Datasets
https://github.com/georgesterpu/Sigmedia-AVSR
공식 코드Attention-based Audio-Visual Fusion for Robust Automatic Speech Recognition
https://github.com/georgesterpu/Taris
공식 코드Learning to Count Words in Fluent Speech enables Online Speech Recognition
https://github.com/gerazov/prosodeep
공식 코드A Variational Prosody Model for the decomposition and synthesis of speech prosody
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.