Msstnet: A Multi-Scale Spatio-Temporal CNN-Transformer Network for Dynamic Facial Expression Recognition

The 49th IEEE International Conference on Acoustics, Speech, & Signal Processing (ICASSP 2024)


Proceedings of the 17th NTCIR Conference on Evaluation of Information Access Technologies

National Institute of Informatics, Tokyo, Japan


DEU-Net: Dual Encoder U-Net for 3D Medical Image Segmentation

The 22nd International Conference on Computer and Information Technology


Research on Creating Buzzing Tweets Through Large Language Models

The 8th International Symposium on Artificial Intelligence and Robotics (ISAIR 2023)


Facial Expression Recognition Using Self-Supervised Learning


CenterMatch: A Center Matching Method for Semi-supervised Facial Expression Recognition

The 6th Chinese Conference on Pattern Recognition and Computer Vision (PRCV 2023)


Learning a Parallel Network for Emotion Recognition Based on Small Training Data

The 8th International Conference on Systems and Informatics (ICSAI 2022)


Resolving Context Contradictions in the Neural Dialogue System based on Sentiment Information

The 7th International Conference on Machine Learning and Soft Computing (ICMLSC2023)


A Study of Response Sentence Generation Considering Topic in Neural Dialogue Model

The 1st International Conference on Communication, Security and Artificial Intelligence (ICCSAI-2022)


Learning a Bimodal Emotion Recognition System Based on Small Amount of Speech Data

The 8th International Conference on Systems and Informatics (ICSAI)


Use Active Learning to Construct Japanese Emoji Emotion Database

Communications in Computer and Information Science


Gait Recognition for Laboratory Safety Management Based on Human Body Pose Model


Emotion-Sentence-DistilBERT: A Sentence-BERT-Based Distillation Model for Text Emotion Classification


2022 8th International Conference on Systems and Informatics (ICSAI)

This paper presents a bimodal emotion recognition system based on the voice and text information using small amount of speech data. Specifically, speech is divided into voice and text to learn emotion classifiers for each modal. The probabilities obtained from these emotion classifiers are weighted based on Mehrabians rule and summed up for each emotion to calculate the final score for bimodal emotion recognition. To create a highly accurate system while solving the problem that there are few Japanese speech data with emotion labels, we propose a novel data augmentation method and employ a transfer learning approach based on a pre-trained VGG16 model and a fine-tuned Bidirectional Encoder Representations from Transformers (BERT) model on the tweets. In order to prove the effectiveness of the proposed method, we revealed the recognition results for 7 emotional states, i.e., anger, sadness, joy, fear, surprise, disgust, and neutral. The experiment result suggested that our novel data augmentation method improved the accuracy and that bimodal predictions based on voice and text-based outperformed the single-model predictions.


Facial Expression Emotion Recognition Based on Transfer Learning and Generative Model

Facial expression emotion recognition has been a popular research topic, which played an important role in assisting the natural human-machine conversation. The conventional method for emotion estimation from facial expressions is to learn a CNN-based image classification model from scratch, However, learning such model requires a large number of labeled facial expression images, which is still a limited resource until now. To solve this problem, we propose a data augmentation method based on StyleGAN2 to generate artificial expression images with respect to seven emotions and use them as the additional training data. We further train an expression emotion recognition model based on a VGG16 network through transfer learning. In this research, we proposed a method using transfer learning and augmented images of facial expressions using trained VGG16 and StyleGAN2 and conducted experiments to achieve higher recognition accuracy for racial expression emotion recognition. Our experiment based on the CFEE dataset suggested that an emotion recognition accuracy of 75.10% could be obtained through transfer learning and the accuracy could further improved to 82.04% with the augmented expression images.


MDSU-Net: A Multi-attention and Depthwise Separable Convolution Network for Stroke Lesion Segmentation

2022 9th International Conference on Biomedical and Bioinformatics Engineering (ICBBE 2022)


Improved Transformer-based Implicit Latent GAN with Multi-headed Self-attention for Unconditional Text Generation

The Fifth International Conference on Intelligence Science (ICIS2022)


TUA1 at eRisk 2022: Exploring Affective Memories for Early Detection of Depression

Experimental IR Meets Multilinguality, Multimodality, and Interaction. Proceedings of the Thirteenth International Conference of the CLEF Association (CLEF 2022)


Classification Method of Surface Defects of Aluminum Profile Based on Transfer Learning

International Conference on Machine Learning and Intelligent Systems Engineering (MLISE 2022)


Proceedings of the 16th NTCIR Conference on Evaluation of Information Access Technologies


Employing Contrastive Strategies for Multi-label Textual Emotion Recognition

12th International Conference on Intelligent Information Processing (IIP2022)


Improving speech emotion recognition by fusing pre-trained and acoustic features using Transformer and BiLSTM


Creating a Japanese dialogue corpus with multi-level topic analysis

2022 4th International Conference on Natural Language Processing


Improvement of Japanese Text Emotion Analysis by Active Learning Using Transformers Language Model

Proceeding of 2022 IEEE 14th International Conference on Computer Research and Development(ICCRD)


Classification of Steel Strip Surface Defects Based on Optimized ResNet18

2021 IEEE International Conference on Agents (ICA)


Thermal Defect Detection and Location for Power Equipment based on Improved VGG16

Proceedings of the 5th IEEE International Conference on Agent


Prediction and Generation of Multiple Complex Drawing Figures From Partial Drawing Sequences

13th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment, and Management


Proceedings of the 15th NTCIR Conference on Evaluation of Information Access Technologies


Building Label-Balanced Emotion Corpus Based On Active Learning for Text Emotion Classification

In Proceedings of 2019 4th International Symposium on Artificial Intelligence and Robotics (ISAIR2019)


Gait recognition in real environment using gait energy image generated by Mask R-CNN

2020 IEEE International Conference on Mechatronics and Automation (ICMA)


Construction of emergency medical support system based on understanding dialect intention

The 15th International Conference on Natural Language Processing and Knowledge Engineering


A fusion model for multi-label emotion classification based on BERT and topic clustering

In International Symposium on Artificial Intelligence and Robotics 2020

SPIE The International Society for Optical Engineering


Speech emotion recognition based on data enhancement in time-frequency domain

International Symposium on Artificial Intelligence and Robotics 2020


Collaborative filtering recommendation algorithm based on bisecting K-means clustering


Examination to develop the artificial intelligence through transforming tacit knowledge of nurses' dialogue for patients with dementia towards explicit knowledge


Surface Defects Classification of Steel Strips based on Transfer Learning and Naive Bayes Model

Proceedings of The 15 th International Conference on Natural Language Processing and Knowledge Engineering (NLP-KE20)


Generation of Musical Scores from Chord Sequences Using Neurodynamic Model

International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems


A Chinese-Japanese Vowel Priority Lip Matching Scheme Based on Humanoid Robot Ren-Xin

In Proceedings of 2020 5th International Symposium on Artificial Intelligence and Robotics (ISAIR2020)


Environment Recognition Using Robot Camera

2020 5th IEEE International Conference on Big Data Analytics (ICBDA)


Investigating voice features for Speech emotion recognition based on four kinds of machine learning methods

Proceedings of 2019 6th IEEE International Conference on Cloud Computing and Intelligence Systems (CCIS2019)


Constructing a Fundamental DevelopmentalDrawing Learning Model Using an Arm Robot


Character action recognition based on deep convolutional neural network and action sequence


ExploringUncertain Samples through Active Learning To Enhance Text Emotion Classification


Text multi-label sentiment analysis based on Bi-LSTM


Capture Important Information for Reading andReasoning by A Two-Pass Attention Mechanism in Dynamic Memory Network


TUA1 at the TREC 2019: Deep Learning Track

Proceedings of 28th Text Retrieval Conference (TREC 2019)

National Institute of Standards and Technology (NIST)


Facial Sentiment Classification Based on Resnet-18 Model

Proceedings of 2019 International Conference on Electronic Engineering and Informatics (EEI)


TUA1 at ImageCLEF 2019 VQA-Med: a Classification and Generation Model based on Transfer Learning


Face and Gender Recognition System Based on Convolutional Neural networks

Proceedings of 2019 IEEE International Conference on Mechatronics and Automation (ICMA)


Text Detection for Natural Scene based on MobileNet V2 and U-Net


Position-Free Hand Gesture Recognition Using Single Shot MultiBox Detector Based Neural Network


Proceedings of the 14th NTCIR Conference


Feature Fusion Based on Neural Image Captioning with Spatial Attention

Proceedings of 2019 the 9th International Workshop on Computer Science and Engineering (WCSE 2019)


Traffic Sign Recognition Based on Up-sampling Convolution


Research on the Effect of Different Speech Segment Lengths on Speech Emotion Recognition Based on LSTM


Emotion recognition for Twitter language based on lingual and expressional information

Proceedings of 2018 5th IEEE International Conference on Cloud Computing and Intelligence Systems (CCIS2018)

Institute of Electrical and Electronics Engineers


Improving LEO Robot ConversationalAbility via Deep Learning Algorithms for 416 Children with Autism


Progressively improving supervised emotion classification through active learning


Emoticon-based emotion analysis for Weibo articles in sentence level


Conference and Labs of the Evaluation Forum (CLEF 2018)


Employing Inception-Resnet-v2 and Bi-LSTM for Medical Domain Visual Question Answering


Sentence Emotion Classification for Intelligent Robotics Based on Word Lexicon and Emoticon Emotions

Proceedings of the International Conference of Intelligent Robotic and Control Engineering


Mining Actionable Intents to Facilitate Search Engine Users' Actions

Proceedings of The 12th International Conference on Natural Language Processing and Knowledge Engineering (NLP-KE17)

Chinese Association for Artificial Intelligence


Recognizing facial emotions in the video


Human Pose Recognition in Robots Based on Angle of Joint Vector


Building Emotional Corpus for Microblogging Emoticons


Realization and Improvement of Robot Object Recognition


Exploring the Relations Between Posts and Comments for Short Text Conversation


RESEARCH ON CONSTRUCTION AND ANALYSIS OF JAPANESE-CHINESE EMOTIONAL EXPRESSION CORPUS


Learning Efficient Drawing Sequence Through Training of Recurrent Neural Network Model


TUA1 at NTCIR-13 Short Text Conversation 2 Task

Proceedings of the 13th NTCIR Conference on Evaluation of Information Access Technologies


Medweb Task: Identify Multi-Symptoms from Tweets Based on Active Learning and Semantic Information


TUA1 at the NTCIR-13 Actionable Knowledge Graph Task: Sampling Related Actions from Online Searching


Shorthand Character Recognition based on Leap Motion Sensor

The 11th International Conference on Natural Language Processing and Knowledge Engineering (NLP-KE'16)


Generation of Humanlike Facial Expression for Natural Human-Robot Interaction System


Disambiguating Users' Temporal Intent in Search Queries with Deep Neural Networks


Proceedings of the 12th NTCIR Conference on Evaluation of Information Access Technologies


KGO at the NTCIR-12 Temporalia Task: Exploring Temporal Information in Search Queries


Understanding Blog author's emotions with hierarchical Bayesian models

2016 IEEE 13th International Conference on Networking, Sensing, and Control (ICNSC)

The research of inferring emotions in natural language is confronted with two major challenges: the lack of basic knowledge in emotion expressions and the co-occurrence of separate emotions through all language unites. In this paper, we propose a Bayesian inference method to explore the basic knowledge with respect to emotion expression in different semantic dimensions, and to infer the co-occurrence of multiple emotion labels through words to the document. Specifically, we incorporate emotions and semantic dimensions as the latent factors in determining the distribution of observed words in a corpus of Blog articles. For each Blog article, we further generalize emotions from words to the document by incorporating a document specific hierarchy in the emotion distributions. The basic knowledge and co-occurred emotion labels in words and documents are obtained through a Gibbs sampling inference. Our experiment is performed on the well-developed Chinese emotion corpus, i.e. Ren-CECps, which indicates both higher accuracy and better robustness in our word and document emotion predictions compared with those generated by the state-of-the-art emotion prediction algorithms, and demonstrates a distribution of emotions in different word semantic dimensions.


Verb-object Selectional Preferences in Chinese Based on Distributional Semantic Model

18th International Conference on Mathematical Methods, Computational Techniques and Intelligent Systems (MAMECTIS '16)

World Scientific and Engineering Academy and Society

In this paper, we propose a approach based on distributional semantic model on selectional preference task in the verb & dobj (direct object) relationship. The distributional representations of words are employed as the semantic feature by using the Word2Vec algorithm. Experimental results show that the proposed approach is effective to discriminate the compatibility of the object words and the performance could be improved by increasing the number of training data. Moreover, the results demonstrate that the semantics is an universal, effective and stable feature in this task, which is consistent with our awareness of using words.


Learning Salient Samples and Distributed Representations for Topic-Based Chinese Message Polarity Classification

Proceedings of the Eighth SIGHAN Workshop on Chinese Language Processing

Association for Computational Linguistics


Proceedings of the 11th NTCIR Conference


Exploring Emotional Words for Chinese Document Chief Emotion Analysis

The 25th Pacific Asia Conference on Language, Information, and Computation (PACLIC25)


Modification Relations based Emotional Keywords Annotation using Conditional Random Fields

The 4th International Conference on Intelligent Networks and Intelligent Systems (ICINIS2011)


Bottom Up: Exploring Word Emotions for Chinese Sentence Chief Sentiment Classification

Proc. IEEE International Conference on Natural Language Processing and Knowledge Engineering

In this paper we demonstrate the effectiveness of employing basic sentiment components for analyzing the chief sentiment of Chinese sentence among nine categories of sentiments (including No emotion). Compared to traditional lexicon based methods, our research explores emotion intensities of words and phrases in an eight dimensional sentiment space as features. An emotion matrix kernel is designed to evaluate inner product of these sentiment features for SVM classification with O(n) time complexity. Experimental result shows our method significantly improves performance of sentiment classification.


A Simple Method Improving Precision of Cross Domain Bilingual Sentence Alignment

International Conference on Advanced Intelligence (ICAI-08)


Exploiting Syntactic and Semantic Information in Coarse Chinese Question Classification

The 4th IEEE International Conference on Natural Language Processing and Knowledge Engineering (NLP-KE)


感情分析のためのカウンセリングマルチモーダルデータセットの構築および評価

感情分析のためのカウンセリングマルチモーダルデータセットの構築および評価

情報処理学会全国大会講演論文集

情報処理学会全国大会講演論文集

コロナ禍をきっかけとして，オンラインカウンセリングが急激に普及した．オンラインカウンセリングは，細かな表情や声色の変化の認識が難しいことが問題点として挙げられる．カウンセラーの判断を助け，業務効率化のために，クライアントの感情の自動分析が有効である．人間は相手の感情を読み取るとき，声色，表情，発話内容など複数の要素から総合的に判断を行っている．AIによる感情推定も同様に，複数の異なるモダリティを組み合わせて用いるマルチモーダル感情推定により，高精度な感情分析が可能になると考えられる．マルチモーダル感情推定には，学習用データとして，感情のラベルが付与されたマルチモーダルデータセットが必要となる．本研究では，オンラインカウンセリング中のクライアントの感情分析のためのマルチモーダルデータセットを構築し，その評価を行う．本データセットには，カウンセラーによる労務者を対象としたオンラインカウンセリングにおける労務者の様子を収録した動画と，第三者により付与された客観感情ラベルが含まれている．


インタビュー対話における問い返し文の生成に関する検討

インタビュー対話における問い返し文の生成に関する検討

言語処理学会 第29回年次大会 発表論文集

言語処理学会 第29回年次大会 発表論文集

遠隔勤務をしているとき，遠隔労働者が自分自身のストレスに気づけないことも多い．精神面の健康状態が深刻になる前に自分自身で気づくことができれば，健康を維持することにつながる．本研究では，遠隔労働者が健康状態をセルフチェックするためのバーチャルエージェント対話システムの構築を目的としている．本稿では，対話時に必要となる「問い返し」の生成手法について考察する．


Relationships Between Client Stress and Multimodal Emotion Estimation in Counseling Situations

クライアントのストレスとカウンセリング場面のマルチモーダ ル感情推定の関連性

JSKE 第18回日本感性工学会春季大会講演論文集

JSKE 第18回日本感性工学会春季大会講演論文集

This study aims to develop a technology to detect the degree of stress of remote workers, which has been increasing in recent years, from multimodal data such as video and audio data during interviews. In this paper, we use interview data obtained in preliminary experiments to analyze the relationship between emotions estimated from facial, audio, and verbal information and stress evaluation by interview. Using the emotion estimation results for each modal based on machine learning algorithm as input, we train a model to predict stress evaluation results, evaluate errors, and confirm the validity of stress evaluation using the emotion estimation results. In addition, by clustering the time-series change patterns of the emotion estimation results, we will analyze whether or not there is a relationship between each type of emotion and stress evaluation.

本研究では，近年増加傾向にあるリモートワーカーのストレス度合いを，面接時の映像・音声データなどのマルチモーダルデータから検出する技術の開発を目指す．本論文では，予備実験で得られたインタビューデータを用いて，顔・音声・言語情報から推定される感情とインタビューによるストレス評価との関係を分析する．機械学習アルゴリズムに基づく各モダルの感情推定結果を入力として，ストレス評価結果の予測，エラー評価，感情推定結果を用いたストレス評価の妥当性確認を行うモデルを学習する．また，感情推定結果の時系列変化パターンをクラスタリングすることで，各感情の種類とストレス評価との関連性の有無を分析する．


HOG特徴量を用いた歩容認識に関する研究

HOG特徴量を用いた歩容認識に関する研究

情報処理学会第85回全国大会

情報処理学会第85回全国大会


Tweet日本語感情コーパスに対するBERTの効果の検証

Tweet日本語感情コーパスに対するBERTの効果の検証

情報処理学会全国大会講演論文集

情報処理学会全国大会講演論文集

大阪大学 豊中キャンパス=>オンライン開催

大阪大学 豊中キャンパス=>オンライン開催


ロボット教師における特定人物の音声の自動生成

ロボット教師における特定人物の音声の自動生成

情報処理学会第83回全国大会講演論文集

情報処理学会第83回全国大会講演論文集


ロボット教師における特定分野のQAシステムの構築

ロボット教師における特定分野のQAシステムの構築

情報処理学会第83回全国大会講演論文集

情報処理学会第83回全国大会講演論文集


神経力学モデルを用いた楽譜の学習とコード系列からの和音生成

神経力学モデルを用いた楽譜の学習とコード系列からの和音生成

第83回情報処理学会全国大会

第83回情報処理学会全国大会


神経力学モデルによる複雑図形の学習と生成

神経力学モデルによる複雑図形の学習と生成

情報処理学会第83回全国大会

情報処理学会第83回全国大会


ロボット教師による特定分野の記述式問題の判定について

ロボット教師による特定分野の記述式問題の判定について

電子情報通信学会総合大会講演論文集

電子情報通信学会総合大会講演論文集


単語の感情属性を活かしたロボット教師の表情生成

単語の感情属性を活かしたロボット教師の表情生成

電子情報通信学会総合大会講演論文集

電子情報通信学会総合大会講演論文集


ロボット教師における特定人物の音声の自動生成

ロボット教師における特定人物の音声の自動生成

電子情報通信学会総合大会講演論文集

電子情報通信学会総合大会講演論文集


ロボット教師における特定分野のQAシステムの構築

ロボット教師における特定分野のQAシステムの構築

電子情報通信学会総合大会講演論文集

電子情報通信学会総合大会講演論文集


深層モデルを用いた画像系列の特徴量自己組織化と映像生成

深層モデルを用いた画像系列の特徴量自己組織化と映像生成

情報処理学会全国大会講演論文集

情報処理学会全国大会講演論文集


構造に注目した神経力学モデルを用いた漢字の筆跡ダイナミクスの学習

構造に注目した神経力学モデルを用いた漢字の筆跡ダイナミクスの学習

情報処理学会全国大会講演論文集

情報処理学会全国大会講演論文集


ペンの持ち上げを考慮した神経力学モデルによる描画図形予測と生成

ペンの持ち上げを考慮した神経力学モデルによる描画図形予測と生成

情報処理学会全国大会講演論文集

情報処理学会全国大会講演論文集


リカレントニューラルネットワークを用いた未学習のコードからの楽譜生成

リカレントニューラルネットワークを用いた未学習のコードからの楽譜生成

情報処理学会全国大会講演論文集

情報処理学会全国大会講演論文集


アームロボットを用いた発達的描画モデルの構築

アームロボットを用いた発達的描画モデルの構築

日本ロボット学会学術講演会

日本ロボット学会学術講演会

社団法人 日本ロボット学会


Kinectを用いた神経力学モデルによる人の身体動作のクラスタリング

Kinectを用いた神経力学モデルによる人の身体動作のクラスタリング

情報処理学会全国大会講演論文集

情報処理学会全国大会講演論文集


深層学習を用いた人の行動認識と感情生成

深層学習を用いた人の行動認識と感情生成

情報処理学会全国大会講演論文集

情報処理学会全国大会講演論文集


アームロボットのための発達的な描画学習モデルの基盤システム構築

アームロボットのための発達的な描画学習モデルの基盤システム構築

情報処理学会全国大会講演論文集

情報処理学会全国大会講演論文集


音符・コード系列に注目した神経力学モデルによる音楽情報の階層的学習

音符・コード系列に注目した神経力学モデルによる音楽情報の階層的学習

情報処理学会全国大会講演論文集

情報処理学会全国大会講演論文集


神経力学モデルを用いた部分描画系列からの描画図形予測

神経力学モデルを用いた部分描画系列からの描画図形予測

情報処理学会全国大会講演論文集

情報処理学会全国大会講演論文集


ペンの持ち上げを考慮した神経力学モデルによる手書き漢字の学習

ペンの持ち上げを考慮した神経力学モデルによる手書き漢字の学習

情報処理学会全国大会講演論文集

情報処理学会全国大会講演論文集


Human Robot Interaction System Based on Emotion State Transition in Continuous Emotion Space

連続感情空間上の感情状態遷移に基づく人間・ロボット対話システム

情報処理学会全国大会講演論文集

情報処理学会全国大会講演論文集


Hierarchical Learning of Primitives Using Neural Network Model

神経回路モデルを用いたプリミティブの階層的学習

情報処理学会全国大会講演論文集

情報処理学会全国大会講演論文集


心的状態遷移ネットワークに基づく感情会話システムの構築

心的状態遷移ネットワークに基づく感情会話システムの構築


Learning Drawing Sequences Using Recurrent Neural Network Model

リカレントニューラルネットワークモデルを用いた図形の描画系列学習

情報処理学会全国大会講演論文集

情報処理学会全国大会講演論文集


Extraction emotion from spoken language based on the language information

言語情報に基づく話言葉の感情抽出に関する研究

The 31st Annual Conference of the Japanese Society for Artificial Intelligence

人工知能学会全国大会第31回


Extraction emotion from spoken language based on the language information

The 31st Annual Conference of the Japanese Society for Artificial Intelligence


言語処理に基づく感情認識

言語処理に基づく感情認識

エンジニアリングフェスティバル 2016

エンジニアリングフェスティバル 2016