[PDF] Top 20 A Model of Zero Shot Learning of Spoken Language Understanding
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A Model of Zero Shot Learning of Spoken Language Understanding
... The model is able to address the adaptivity is- sues because the utterance and the dialogue act representations are in the same space using the same shared parameters φ(w), which are ini- tialised with ... See full document
6
A Self Attentive Model with Gate Mechanism for Spoken Language Understanding
... Spoken Language Understanding (SLU), which typically involves intent determination and slot filling, is a core component of spoken dialogue ...Joint learning has shown to be effective ... See full document
10
Integrating Prosodics into a Language Model for Spoken Language Understanding of Thai
... a spoken language understanding system for ...the model is designed to integrate prosodics into a language model based on constraint dependency ... See full document
10
Class specific synthesized dictionary model for Zero Shot Learning
... Zero-shot learning (ZSL) aims at recognizing unseen classes that are absent during the training ...embedding model to bridge the low-level visual space and the high-level class prototype ... See full document
9
Locale agnostic Universal Domain Classification Model in Spoken Language Understanding
... classification model for each new locale, and it brings two challenging issues: 1) having a separate model per locale becomes a bot- tleneck for rapid scaling of virtual assistant due to the resource and ... See full document
7
Zero-Shot Learning of Language Models for Describing Human Actions Based on Semantic Compositionality of Actions
... Zero-shot learning has recently become a popular research topic in machine learning, in particular in the domain of large scale visual object recognition and image ...Hence ... See full document
8
Zero Shot Transfer Learning for Event Extraction
... In this work, we take a fresh look at the event ex- traction task and model it as a generic ground- ing problem. We propose a transferable neu- ral architecture, which leverages existing human- constructed event ... See full document
11
From Zero-Shot Learning to Cold-Start Recommendation
... Zero-shot learning (ZSL) and cold-start recommendation (CSR) are two challenging problems in computer vision and recommender system, respectively. In general, they are inde- pendently investigated in ... See full document
8
Semantic embeddings of generic objects for zero-shot learning
... increase zero-shot recogni- tion accuracy? This is difficult to assess, but two different observations suggest otherwise: First, no graph embed- ding outperform the trivial solution; second, BabelNet is a ... See full document
14
Synthesizing Samples fro Zero shot Learning
... machine learning and computer vision ...many zero-shot learning (ZSL) approach- es have been proposed [Akata et ...classification model can be built even without any labeled samples for ... See full document
7
Structured Learning for Context aware Spoken Language Understanding of Robotic Commands
... machine learning depends on such percep- tual information, thus inducing the contextual pre- conditions of the involved disambiguation choices from real examples, ...domain-independent model of grounded ... See full document
10
Unsupervised Transfer Learning for Spoken Language Understanding in Intelligent Agents
... ELMoL language model train- ing is carried out similar to ...multi-task model, there is only 1 LSTM layer with 200 hidden ...the model was trained on IUD with a batch size of 128 for 25 ... See full document
8
Spoken Language Understanding: from Spoken Utterances to Semantic Structures
... unigram model had comparable performance to the bigram and trigram feature ...unigram model, having ...the spoken dialogue system ...the model has been trained to be used in the SDS, ... See full document
148
Zero shot Learning of Classifiers from Natural Language Quantification
... Provided data consisting of statements labeled with logical forms, the model can be trained via maximum likelihood estimation, and be used to predict interpretations for new statements. For training this ... See full document
11
Few Shot and Zero Shot Learning for Historical Text Normalization
... MTL model for each of the 64 different sharing ...MTL model achieves a normal- ization accuracy of 75.9%, while the worst model gets ...single-task model, showing the general effec- tiveness ... See full document
11
Active Learning in Noisy Conditions for Spoken Language Understanding
... As seen in Figure 2(a), the center of the distribution in terms of density is the darkest part. Also, the distribution of instances is not uniform at all, and excluding any part of the distribution especially parts ... See full document
10
A Weakly Supervised Learning Approach for Spoken Language Understanding
... vised learning approach for spoken lan- guage understanding in domain-specific dialogue ...We model the task of spoken language understanding as a suc- cessive ... See full document
9
Towards Zero shot Language Modeling
... the model with this side information ...non-conditional language model with a universal prior (B ARE ) to a series of architectures conditioned on language-specific properties that have been ... See full document
11
Zero-Shot Adaptive Transfer for Conversational Language Understanding
... their language understanding ca- pabilities by adding new ...novel Zero-Shot Adaptive Transfer method for slot tagging that utilizes the slot description for transferring reusable con- cepts ... See full document
8
Survey and Analysis on Language Translator using Neural Machine Translation
... Deep learning applications was first appeared in speech recognition in ...NMT, Zero-Resource NMT, Google, Fully Character-NMT, Zero-Shot NMT in ...NMT model are trained jointly ...deep ... See full document
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