A PyTorch-based Speech Toolkit

End-to-End Speech Processing Toolkit

On-device Speech-to-Intent engine powered by deep learning

ICASSP 2023-2024 Papers: A complete collection of influential and exciting research papers from the ICASSP 2023-24 conferences. Explore the latest advancements in acoustics, speech and signal processing. Code included. Star the repository to support the advancement of audio and signal processing!

Slot-Gated Modeling for Joint Slot Filling and Intent Prediction

Open source code for EMNLP-19 Paper "A Stack-Propagation Framework with Token-Level Intent Detection for Spoken Language Understanding".

Open source code for EMNLP 2020 Findings Paper "AGIF: An Adaptive Graph-Interactive Framework for Joint Multiple Intent Detection and Slot Filling"

Dataset Release for Intent Classification from Speech

Open source code and data for AAAI 2022 Oral Paper "Text is no more Enough! A Benchmark for Profile-based Spoken Language Understanding"

EMNLP-2020: Cross-lingual Spoken Language Understanding with Regularized Representation Alignment

Source code for ACL 2020 paper "Learning Spoken Language Representations with Neural Lattice Language Modeling"

ITALIC: An ITALian Intent Classification Dataset

FastLongSpeech is a novel framework designed to extend the capabilities of Large Speech-Language Models for efficient long-speech processing without necessitating dedicated long-speech training data.

Semi-supervised spoken language understanding (SLU) via self-supervised speech and language model pretraining

Source code for ASRU 2019 paper "Adapting Pretrained Transformer to Lattices for Spoken Language Understanding"

This repo contains the code for <<"Alexa, can you forget me?” Machine Unlearning Benchmark on Spoken Language Understanding>>

A general purpose task-agnostic speech augmentation policy

A TensorFlow implement for "A Stack-Propagation Framework with Token-Level Intent Detection for Spoken Language Understanding".

Source code and data for the journal ``Dual learning for semi-supervised natural language understanding" in TASLP 2020.

"An Investigation of the Combination of Rehearsal and Knowledge Distillation in Continual Learning for Spoken Language Understanding", accepted at INTERSPEECH 2023.