A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2017; you can also visit the original URL.
The file type is application/pdf.
Filters
Specialized Language Models using Dialogue Predictions
[article]
1996
arXiv
pre-print
Preserved Fulltext
Other Versions
The use of several language models obtained by exploiting dialogue predictions gives better results than the use of a single model for the whole dialogue interaction. ...
This paper analyses language modeling in spoken dialogue systems for accessing a database. ...
Table 1 : Results of single models and models with DP.
SINGLE CONTEXT-INDEPENDENT MODELS
LANGUAGE MODELS WITH DIALOGUE PREDICTIONS A set of two models with DP were tested. ...
arXiv:cmp-lg/9612002v2
fatcat:zndyktpa2jgzhnn5k5dp3vketu
Specialized language models using dialogue predictions
1997 IEEE International Conference on Acoustics, Speech, and Signal Processing
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2017; you can also visit the original URL.
The file type is application/pdf.
The use of several language models obtained by exploiting dialogue predictions gives better results than the use of a single model for the whole dialogue interaction. ...
This paper analyses language modeling in spoken dialogue systems for accessing a database. ...
Single context-independent models
SA
Language models with dialogue predictions A set of two models with DP were tested. The first one, ALL_PRED, was created as described in Section 3.2. ...
doi:10.1109/icassp.1997.596055
dblp:conf/icassp/PopoviciB97
fatcat:zofjt6o6vjgvng3fbce4iwozee
DSBERT:Unsupervised Dialogue Structure learning with BERT
[article]
2021
arXiv
pre-print
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2021; you can also visit the original URL.
The file type is application/pdf.
can be used for dialogue structure learning. ...
Unsupervised dialogue structure learning is an important and meaningful task in natural language processing. ...
The encoder of DSBERT only uses the features of special token to predict the latent states. In the decode stage, we also only use the features of special token to restore the dialogue. ...
arXiv:2111.04933v1
fatcat:7fcj7mfkrrbhpl6os73ppoxjee
CAiRE: An Empathetic Neural Chatbot
[article]
2020
arXiv
pre-print
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf.
Other Versions
., 2019) learning approach that fine-tunes a large-scale pre-trained language model with multi-task objectives: response language modeling, response prediction and dialogue emotion detection. ...
We evaluate our model on the recently proposed empathetic-dialogues dataset (Rashkin et al., 2019), the experiment results show that CAiRE achieves state-of-the-art performance on dialogue emotion detection ...
objectives: response language modeling, response prediction, and dialogue emotion detection. ...
arXiv:1907.12108v4
fatcat:4qh7cs5un5chjp3wrxy3uqlthe
TOD-BERT: Pre-trained Natural Language Understanding for Task-Oriented Dialogue
[article]
2020
arXiv
pre-print
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf.
Other Versions
The underlying difference of linguistic patterns between general text and task-oriented dialogue makes existing pre-trained language models less useful in practice. ...
, dialogue act prediction, and response selection. ...
Figure 1 : 1 Dialogue pre-training based on Transformer encoder with user and system special tokens. Two objective functions are used: masked language modeling and response contrastive learning. ...
arXiv:2004.06871v3
fatcat:plfdyo7j3nfdhiqdrztyzbou3m
Goal-Oriented Multi-Task BERT-Based Dialogue State Tracker
[article]
2020
arXiv
pre-print
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf.
The organizers introduced the Schema-Guided Dialogue (SGD) dataset with multi-domain conversations and released a zero-shot dialogue state tracking model. ...
The model "queries" dialogue history with descriptions of slots and services as well as possible values of slots. ...
To predict a dialogue state update, our model solves several classification tasks and a span-prediction task. ...
arXiv:2002.02450v1
fatcat:2mwuotfnsrhdvhk7cfjmlzla44
Different Strokes for Different Folks: Investigating Appropriate Further Pre-training Approaches for Diverse Dialogue Tasks
[article]
2021
arXiv
pre-print
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2021; you can also visit the original URL.
The file type is application/pdf.
Loading models pre-trained on the large-scale corpus in the general domain and fine-tuning them on specific downstream tasks is gradually becoming a paradigm in Natural Language Processing. ...
However, most of these further pre-training works just keep running the conventional pre-training task, e.g., masked language model, which can be regarded as the domain adaptation to bridge the data distribution ...
prediction (DSP), context response matching (CRM), and dialogue coherence verification (DCV), each of which has special characteristics. ...
arXiv:2109.06524v1
fatcat:bjxrje5ryfhrde3ehcnwsq3o2i
The SPPD System for Schema Guided Dialogue State Tracking Challenge
[article]
2020
arXiv
pre-print
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf.
The key components of the system is a number of BERT based zero-shot NLU models that can effectively capture semantic relations between natural language descriptions of services' schemas and utterances ...
from dialogue turns. ...
For each user turn of a dialogue, the proposed dialogue state tracking model must make predictions for all three fields, and metrics mentioned above are used to evaluate the model predictions. ...
arXiv:2006.09035v1
fatcat:khqmburmrbbtldl45cltlpovju
STN4DST: A Scalable Dialogue State Tracking based on Slot Tagging Navigation
[article]
2021
arXiv
pre-print
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2021; you can also visit the original URL.
The file type is application/pdf.
Other Versions
extract slot value quickly and accurately by the joint learning of slot tagging and slot value position prediction in the dialogue context, especially for unknown slot values. ...
Extensive experiments over several benchmark datasets show that the proposed model performs better than state-of-the-art baselines greatly. ...
When dealing with more complex unknown slot values, STN4DST presents better generalization and scalability than the widely used span extraction, showing greater research potential and application prospect ...
arXiv:2010.10811v2
fatcat:rgdb64ncbndnnbijhntf3h4tyi
DIA-MOLE: An Unsupervised Learning Approach to Adaptive Dialogue Models for Spoken Dialogue Systems
1997
arXiv
pre-print
Preserved Fulltext
The Internet Archive has a preservation copy of this work in our general collections.
The file type is application/pdf.
The DIAlogue MOdel Learning Environment supports an engineering-oriented approach towards dialogue modelling for a spoken-language interface. ...
Major steps towards dialogue models is to know about the basic units that are used to construct a dialogue model and possible sequences. ...
E.g. the word recognizer may use dialogue act predictions to choose a specific language model trained on these DDA classes to improve word recognition. ...
arXiv:cmp-lg/9708009v1
fatcat:zog4bfysyreqnpximemhicboq4
The Use of Psycholinguistic Patterns in Interactive Systems of Active Information Retrieval
2018
International Journal of Engineering & Technology
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf.
The article explores the possibility of using psycholinguistic patterns in a dialogue with the Internet visitors. ...
The model of building psycholinguistic patterns for revealing the semantic information in dialogues is given. Patterns are based on associative links of words and word combinations. ...
Conclusion As research shows the possibility of using specialized psycholinguistic patterns increases the level of interaction between the user and the machine, since they allow dialogue in the natural ...
doi:10.14419/ijet.v7i4.38.24595
fatcat:iojc3pq3jfg6jfczjswhlkgvyq
Affect Recognition for Multimodal Natural Language Processing
2020
Cognitive Computation
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf.
Acknowledgments The guest editors are grateful to the Editor-in-Chief, Amir Hussain, and to the many reviewers who kindly agreed to serve for this special issue and submitted their insightful reviews in ...
It expands the horizons of NLP to study language used in face to face communication and in online multimedia. ...
The challenges of modeling human multimodal language can be split into two major categories: (1) studying each modality individually and modeling each in a manner that can be linked to other modalities ...
doi:10.1007/s12559-020-09738-0
fatcat:lmospfzn3barvk6fwnnk2rvw3i
Amendable Generation for Dialogue State Tracking
[article]
2021
arXiv
pre-print
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2021; you can also visit the original URL.
The file type is application/pdf.
With the additional amending generation pass, our model is tasked to learn more robust dialogue state tracking by amending the errors that still exist in the primitive dialogue state, which plays the role ...
The mistakes of these models made at the current turn are prone to be carried over to the next turn, causing error propagation. ...
Besides, some methods treat dialogue state tracking as a causal language model by using the dialogue of the current turn and previous dialogue state as input sequence (Lin et al., 2020; . ...
arXiv:2110.15659v1
fatcat:g6dxqmm4dzd7fibipomrdc4w2y
Deal or No Deal? End-to-End Learning of Negotiation Dialogues
2017
Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf.
For the first time, we show it is possible to train end-to-end models for negotiation, which must learn both linguistic and reasoning skills with no annotated dialogue states. ...
dialogue. ...
Acknowledgments We would like to thank Luke Zettlemoyer and the anonymous EMNLP reviewers for their insightful comments, and the Mechanical Turk workers who helped us collect data.
References ...
doi:10.18653/v1/d17-1259
dblp:conf/emnlp/LewisYDPB17
fatcat:t32yw2avuzed5mms7a45ag2tyq
Dialogue State Tracking with a Language Model using Schema-Driven Prompting
[article]
2021
arXiv
pre-print
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2021; you can also visit the original URL.
The file type is application/pdf.
Recently, good results have been obtained using more general architectures based on pretrained language models. ...
Here, we introduce a new variation of the language modeling approach that uses schema-driven prompting to provide task-aware history encoding that is used for both categorical and non-categorical slots ...
Moreover, using descriptions consistently improves the performance of both models. All our models outperform baselines that do not use extra dialogue data. ...
arXiv:2109.07506v1
fatcat:vda2nn7f55etneaxe5ugv47zvi
« Previous
Showing results 1 — 15 out of 85,364 results