1 citations · 1 across the 3 of their papers we have counts for
3 papers
cs.CL2024
Coupling Speech Encoders with Downstream Text Models
Ciprian Chelba, Johan Schalkwyk
We present a modular approach to building cascade speech translation (AST) models that guarantees that the resulting model performs no worse than the 1-best cascade baseline while…
cs.CL2023★ 1 cited
SLM: Bridge the thin gap between speech and text foundation models
Mingqiu Wang, Wei Han, Izhak Shafran +15
We present a joint Speech and Language Model (SLM), a multitask, multilingual, and dual-modal model that takes advantage of pretrained foundational speech and language models. SLM…
cs.CL2023
Lego-Features: Exporting modular encoder features for streaming and deliberation ASR
Rami Botros, Rohit Prabhavalkar, Johan Schalkwyk +3
In end-to-end (E2E) speech recognition models, a representational tight-coupling inevitably emerges between the encoder and the decoder. We build upon recent work that has begun to…