https://github.com/roman-vygon/triplet_loss_kws
공식 코드Learning Efficient Representations for Keyword Spotting with Triplet Loss
Papers with Code 아카이브
Keyword Spotting
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
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- 평가표
- 10
- 보존된 평가 기록
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In speech processing, keyword spotting deals with the identification of keywords in utterances.
<span style="color:grey; opacity: 0.6">( Image credit: Simon Grest )</span>
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/s3prl/s3prl
공식 코드TERA: Self-Supervised Learning of Transformer Encoder Representation for Speech
https://github.com/sara-ahmed/asit
공식 코드ASiT: Local-Global Audio Spectrogram vIsion Transformer for Event Classification
https://github.com/siavashshams/ssamba
공식 코드SSAMBA: Self-Supervised Audio Representation Learning with Mamba State Space Model
https://github.com/sumansamui/small-footprint-keyword-spotting
공식 코드https://github.com/swagshaw/rainbow-keywords
공식 코드Rainbow Keywords: Efficient Incremental Learning for Online Spoken Keyword Spotting
https://github.com/tae-jun/temporal-feedback-crnn
공식 코드Temporal Feedback Convolutional Recurrent Neural Networks for Speech Command Recognition
https://github.com/tvanh512/importantAug
공식 코드https://github.com/ujjwal-9/celestini-dl
공식 코드Indian EmoSpeech Command Dataset: A dataset for emotion based speech recognition in the wild
https://github.com/umbertomichieli/tap-slda
공식 코드https://github.com/wenet-e2e/wekws
공식 코드WeKws: A production first small-footprint end-to-end Keyword Spotting Toolkit
https://github.com/wilkinghoff/kws-dailytalk
공식 코드https://github.com/wngh1187/ipet
공식 코드Integrated Parameter-Efficient Tuning for General-Purpose Audio Models
https://github.com/x-lance/kwstreamingsearch
공식 코드MFA-KWS: Effective Keyword Spotting with Multi-head Frame-asynchronous Decoding
https://github.com/xiaomi-research/dasheng-glap
공식 코드GLAP: General contrastive audio-text pretraining across domains and languages
https://github.com/592595/TERA
TERA: Self-Supervised Learning of Transformer Encoder Representation for Speech
https://github.com/Abdallah-Hesham99/tell_your_motor_speed
Speech Commands: A Dataset for Limited-Vocabulary Speech Recognition
https://github.com/Alex-Riviello/KWS_MCU
Temporal Convolution for Real-time Keyword Spotting on Mobile Devices
https://github.com/Alpe6825/Unicornn
Speech Commands: A Dataset for Limited-Vocabulary Speech Recognition
https://github.com/AmirmohammadRostami/ASV-anti-spoofing-with-EABN
EfficientNet-Absolute Zero for Continuous Speech Keyword Spotting
https://github.com/Anustup900/Tensorflow-Speech-Recognition
https://github.com/Arizona-Voice/Arizona-spotting
Keyword Transformer: A Self-Attention Model for Keyword Spotting
https://github.com/Arizona-Voice/blossom
https://github.com/Benja1972/Speech_recognition_Tensorflow2.0
Speech Commands: A Dataset for Limited-Vocabulary Speech Recognition
https://github.com/BgLoveXixi/Keyword_recognition
https://github.com/Cbhihe/classify_sound_mobile
Speech Commands: A Dataset for Limited-Vocabulary Speech Recognition
https://github.com/DataSenseiAryan/GoogleSpeechCommandLowFootprint
https://github.com/EscVM/EscVM_YT/blob/master/Notebooks/1%20-%20TF2.X%20DeepAI-Quickie/tf_2_keyword_transformer.ipynb
Keyword Transformer: A Self-Attention Model for Keyword Spotting
https://github.com/FraCorti/Deep_Subnetworks_for_Dynamic_Resource_Constraints
https://github.com/ID56/Torch-KWT
Keyword Transformer: A Self-Attention Model for Keyword Spotting
https://github.com/Jaskaran197/KWS-TF-MCU
https://github.com/Kirili4ik/kws-attention-pytorch
Attention-based End-to-End Models for Small-Footprint Keyword Spotting
https://github.com/KrishnaDN/Keyword-Transformer
Keyword Transformer: A Self-Attention Model for Keyword Spotting
https://github.com/Lebhoryi/ML-KWS-for-MCU
https://github.com/PaddlePaddle/DeepSpeech
https://github.com/Pandade1997/tera_asvproof
TERA: Self-Supervised Learning of Transformer Encoder Representation for Speech
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.