Librispeech Transducer Model with Internal Language Model Prior Correction
원문 초록
We present our transducer model on Librispeech. We study variants to include an external language model (LM) with shallow fusion and subtract an estimated internal LM. This is justified by a Bayesian interpretation where the transducer model prior is given by the estimated internal LM. The subtraction of the internal LM gives us over 14% relative improvement over normal shallow fusion. Our transducer has a separate probability distribution for the non-blank labels which allows for easier combination with the external LM, and easier estimation of the internal LM. We additionally take care of including the end-of-sentence (EOS) probability of the external LM in the last blank probability which further improves the performance. All our code and setups are published.
함께 살펴볼 논문
공통 태그를 근거로 연결했습니다. 실제 인용 관계나 논문의 우수성을 뜻하지 않습니다.
Making Language Model a Hierarchical Classifier and Generator
Data Efficacy for Language Model Training
Enterprise Large Language Model Evaluation Benchmark
Research on Model Parallelism and Data Parallelism Optimization Methods in Large Language Model-Based Recommendation Systems
LM-SPT: LM-Aligned Semantic Distillation for Speech Tokenization
Finance Language Model Evaluation (FLaME)
토론
이 논문과 연결된 포럼 글이 아직 없습니다.