92 citations · 523 across the 22 of their papers we have counts for
7 papers · 1 filter
Joint Online Spoken Language Understanding and Language Modeling with Recurrent Neural Networks
Bing Liu, Ian Lane
Speaker intent detection and semantic slot filling are two critical tasks in spoken language understanding (SLU) for dialogue systems. In this paper, we describe a recurrent neural…
Attention-Based Recurrent Neural Network Models for Joint Intent Detection and Slot Filling
Bing Liu, Ian Lane
Attention-based encoder-decoder neural network models have recently shown promising results in machine translation and speech recognition. In this work, we propose an attention-bas…
An Approach for Self-Training Audio Event Detectors Using Web Data
Benjamin Elizalde, Ankit Shah, Siddharth Dalmia +5
Audio Event Detection (AED) aims to recognize sounds within audio and video recordings. AED employs machine learning algorithms commonly trained and tested on annotated datasets. H…
Experiments on the DCASE Challenge 2016: Acoustic Scene Classification and Sound Event Detection in Real Life Recording
Benjamin Elizalde, Anurag Kumar, Ankit Shah +4
In this paper we present our work on Task 1 Acoustic Scene Classi- fication and Task 3 Sound Event Detection in Real Life Recordings. Among our experiments we have low-level and hi…
City-Identification of Flickr Videos Using Semantic Acoustic Features
Benjamin Elizalde, Guan-Lin Chao, Ming Zeng +1
City-identification of videos aims to determine the likelihood of a video belonging to a set of cities. In this paper, we present an approach using only audio, thus we do not use a…
AudioPairBank: Towards A Large-Scale Tag-Pair-Based Audio Content Analysis
Sebastian Sager, Benjamin Elizalde, Damian Borth +3
Recently, sound recognition has been used to identify sounds, such as car and river. However, sounds have nuances that may be better described by adjective-noun pairs such as slow…
Environmental Noise Embeddings for Robust Speech Recognition
Suyoun Kim, Bhiksha Raj, Ian Lane
We propose a novel deep neural network architecture for speech recognition that explicitly employs knowledge of the background environmental noise within a deep neural network acou…