論文: SPEECH-TRANSFORMER: A NO-RECURRENCE SEQUENCE-TO-SEQUENCE MODELFOR SPEECH RECOGNITION ...
論文: Deep FSMN for Large Vocabulary Continuous Speech Recognition 思想: 對於大詞匯量語音識別,往往需要更深的網絡結構,但是當FSMN 或cFSMN 的結構很深時容易引發剃度消失和爆炸問題 於是本文對cFSMN結構進一步改進,對序列記憶模塊之間引入skip connection,保證信息在更深的層之間傳播,緩解剃度消失和爆炸的問題 ...
2020-09-16 21:51 0 863 推薦指數:
論文: SPEECH-TRANSFORMER: A NO-RECURRENCE SEQUENCE-TO-SEQUENCE MODELFOR SPEECH RECOGNITION ...
LAS: listen, attented and spell,Google 思想: sequence to sequence的思想,模型分為encoder和dec ...
論文: EESEN:END-TO-END SPEECH RECOGNITION USING DEEP RNN MODELS AND WFST-BASED DECODING ...
論文: CTC:Connectionist Temporal Classification: Labelling Unsegmented Sequence Data with Recurrent Neural Networks 思想: 語音識別中,一般包含語音 ...
的時序長度,在大規模語音數據訓練時提升計算效率; 2)decoder輸入采樣策略,如果訓練時 ...
論文: TRANSFORMER-TRANSDUCER:END-TO-END SPEECH RECOGNITION WITH SELF-ATTENTION 思想: 1)借助RNN-T在語音識別上的優勢,通過tranformer替換RNN-T中的RNN結構,實現 ...
論文: A time delay neural network architecture for efficient modeling of longtemporal contexts ...
論文: TRANSFORMER TRANSDUCER: A STREAMABLE SPEECH RECOGNITION MODELWITH TRANSFORMER ENCODERS A ...