Dec 15, 2020 · In this work, we propose an E2E system that is designed to jointly train on multiple speech-to-text tasks, such as ASR (speech-transcription) ...
Traditional SLU systems consist of a two-stage pipeline, an Automatic Speech Recognition (ASR) component that processes customer speech and generates a text ...
Dec 15, 2020 · This work proposes an E2E system that is designed to jointly train on multiple speech-to-text tasks, such as ASR (speech-transcription) and ...
This work investigates speaker adaptation and transfer learning for spoken language understanding (SLU). We focus on the direct extraction of semantic tags from ...
Oct 9, 2023 · ABSTRACT. A number of methods have been proposed for End-to-End. Spoken Language Understanding (E2E-SLU) using pre-.
[PDF] WhiSLU: End-to-End Spoken Language Understanding with ...
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Aug 24, 2023 · We introduce WhiSLU, an end-to-end SLU model that lever- ages sequence-level multitask learning to perform transfer learning with the pretrained ...
A novel training method is proposed that enables pretrained contextual embeddings to process acoustic features and is based on the teacher-student framework ...
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"
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Snips-SmartLights Benchmark (Spoken Language Understanding)
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Exploring Transfer Learning For End-to-End Spoken Language Understanding ... Using Speech Synthesis to Train End-to-End Spoken Language Understanding Models.
Spoken language understanding (SLU) is a critical component in task-oriented dialogue systems. It usually consists of intent and slot filling task.
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