Learning influences fromword use in polylogue

Tomoharu Iwata; Shinji Watanabe

Learning influences fromword use in polylogue

Tomoharu Iwata^*, Shinji Watanabe

^*Corresponding author for this work

Research output: Contribution to journal › Conference article › peer-review

2 Citations (Scopus)

Abstract

We propose a probabilistic model for estimating influences among speakers from conversation data with multiple people. In conversations, people tend to mimic their companions' behavior depending on their level of trust. With the proposed model, we assume that the word use of a speaker depends on the word use of previous speakers as well as their own earlier word use and the general word distribution. The influences can be efficiently estimated by using the expectation maximization (EM) algorithm. Experiments on two meeting data sets in Japanese and in English demonstrate the effectiveness of the proposed method.

Original language	English
Pages (from-to)	3089-3092
Number of pages	4
Journal	Proceedings of the Annual Conference of the International Speech Communication Association, INTERSPEECH
Publication status	Published - 2011
Externally published	Yes
Event	12th Annual Conference of the International Speech Communication Association, INTERSPEECH 2011 - Florence, Italy Duration: 2011 Aug 27 → 2011 Aug 31

Keywords

Conversation analysis
Influence
Latent variable model

ASJC Scopus subject areas

Language and Linguistics
Human-Computer Interaction
Signal Processing
Software
Modelling and Simulation

Cite this

@article{65d1e318fd314830a113f756dccc47dc,

title = "Learning influences fromword use in polylogue",

abstract = "We propose a probabilistic model for estimating influences among speakers from conversation data with multiple people. In conversations, people tend to mimic their companions' behavior depending on their level of trust. With the proposed model, we assume that the word use of a speaker depends on the word use of previous speakers as well as their own earlier word use and the general word distribution. The influences can be efficiently estimated by using the expectation maximization (EM) algorithm. Experiments on two meeting data sets in Japanese and in English demonstrate the effectiveness of the proposed method.",

keywords = "Conversation analysis, Influence, Latent variable model",

author = "Tomoharu Iwata and Shinji Watanabe",

year = "2011",

language = "English",

pages = "3089--3092",

journal = "Proceedings of the Annual Conference of the International Speech Communication Association, INTERSPEECH",

issn = "2308-457X",

note = "12th Annual Conference of the International Speech Communication Association, INTERSPEECH 2011 ; Conference date: 27-08-2011 Through 31-08-2011",

}

TY - JOUR

T1 - Learning influences fromword use in polylogue

AU - Iwata, Tomoharu

AU - Watanabe, Shinji

PY - 2011

Y1 - 2011

N2 - We propose a probabilistic model for estimating influences among speakers from conversation data with multiple people. In conversations, people tend to mimic their companions' behavior depending on their level of trust. With the proposed model, we assume that the word use of a speaker depends on the word use of previous speakers as well as their own earlier word use and the general word distribution. The influences can be efficiently estimated by using the expectation maximization (EM) algorithm. Experiments on two meeting data sets in Japanese and in English demonstrate the effectiveness of the proposed method.

AB - We propose a probabilistic model for estimating influences among speakers from conversation data with multiple people. In conversations, people tend to mimic their companions' behavior depending on their level of trust. With the proposed model, we assume that the word use of a speaker depends on the word use of previous speakers as well as their own earlier word use and the general word distribution. The influences can be efficiently estimated by using the expectation maximization (EM) algorithm. Experiments on two meeting data sets in Japanese and in English demonstrate the effectiveness of the proposed method.

KW - Conversation analysis

KW - Influence

KW - Latent variable model

UR - http://www.scopus.com/inward/record.url?scp=84865749839&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84865749839&partnerID=8YFLogxK

M3 - Conference article

AN - SCOPUS:84865749839

SN - 2308-457X

SP - 3089

EP - 3092

JO - Proceedings of the Annual Conference of the International Speech Communication Association, INTERSPEECH

JF - Proceedings of the Annual Conference of the International Speech Communication Association, INTERSPEECH

T2 - 12th Annual Conference of the International Speech Communication Association, INTERSPEECH 2011

Y2 - 27 August 2011 through 31 August 2011

ER -

Learning influences fromword use in polylogue

Abstract

Keywords

ASJC Scopus subject areas

Other files and links

Fingerprint

Cite this