Apr 7, 2019 � Title:Speech Model Pre-training for End-to-End Spoken Language Understanding ... Abstract: Whereas conventional spoken language understanding (SLU)�...
Feb 11, 2021 � Abstract:End-to-end (E2E) spoken language understanding (SLU) can infer semantics directly from speech signal without cascading an automatic�...
In this paper, we propose to unify a well-optimized E2E ASR encoder. (speech) and a pre-trained language model encoder (language) into a transformer decoder.
A method to reduce the data requirements of end-to-end SLU in which the model is first pre-trained to predict words and phonemes, thus learning good�...
Spoken language understanding (SLU) systems infer the meaning or intent of a spoken utterance [1]. This is crucial for voice user interfaces, in which the�...
The proposed unified speech-language pre-trained model (SLP) is continually enhanced on limited labeled data from a target domain by using a conditional�...
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What is the end-to-end speech model?
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This setup is appealing for building virtual AI assistants as maintaining a separate large specialized model for each task is not computationally efficient.
This repo contains PyTorch code for training end-to-end SLU models used in the papers "Speech Model Pre-training for End-to-End Spoken Language Understanding"�...
Spoken language understanding (SLU) re- quires a model to analyze input acoustic sig- nal to understand its linguistic content and make predictions.
Sep 14, 2024 � In this paper, we propose to unify a well-optimized E2E ASR encoder (speech) and a pre-trained language model encoder (language) into a�...
