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Continual learning on audio scene classification using representative data and memory replay GANs 査読国際共著国際誌

Ibnu Daqiqil ID, Masanobu Abe, Sunao Hara

Bulletin of Electrical Engineering and Informatics 14 ( 1 ) 568 - 580 2025年2月

担当区分：最終著者記述言語：英語掲載種別：研究論文（学術雑誌）出版者・発行元：Institute of Advanced Engineering and Science

This paper proposes a methodology aimed at resolving catastropic forgetting problem by choosing a limited portion of the historical dataset to act as a representative memory. This method harness the capabilities of generative adversarial networks (GANs) to create samples that expand upon the representative memory. The main advantage of this method is that it not only prevents catastrophic forgetting but also improves backward transfer and has a relatively stable and small size. The experimental results show that combining real representative data with artificially generated data from GANs, yielded better outcomes and helped counteract the negative effects of catastrophic forgetting more effectively than solely relying on GAN-generated data. This mixed approach creates a richer training environment, aiding in the retention of previous knowledge. Additionally, when comparing different methods for selecting data as the proportion of GAN-generated data increases, the low probability and mean cluster methods performed the best. These methods exhibit resilience and consistency by selecting more informative samples, thus improving overall performance.

DOI： 10.11591/eei.v14i1.8127

OtologMap: a case study on the construction of an environmental sound map recorded by smart devices at Okayama and Kurashiki 査読国際誌

Sunao Hara, Masanobu Abe

Noise Control Engineering Journal 1 - 12 2025年2月

Explicit Prosody Control to Realize Discourse Focus in End-to-End Text-to-Speech 査読国際誌

Takumi WADA, Sunao HARA, Masanobu ABE

IEEE International Workshop on Machine Learning for Signal Processing 2024年9月

Speech Synthesis Using Ambiguous Inputs From Wearable Keyboards 査読国際誌

Matsuri Iwasaki, Sunao Hara, Masanobu Abe

2023 Asia Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC 2023) 1172 - 1178 2023年11月

記述言語：英語掲載種別：研究論文（国際会議プロシーディングス）

This paper proposes a new application in speech communication using text-to-speech (TTS), and the goal is to enable dysarthria, articulation disorder, or persons who have difficulty in speaking to communicate anywhere and anytime using speech to express their thoughts and feelings. To achieve this goal, an input method is required. Thus, we propose a new text-entry method based on three concepts. First, from an easy-to-carry perspective, we used a wearable keyboard that inputs digits from 0 to 9 in decimal notation according to 10-finger movements. Second, from a no-training perspective, users input sentences in a way of touch typing using the wearable keyboard. Following this method, we obtained a sequence of numbers corresponding to the sentence. Third, a neural machine translation (NMT) method is applied to estimate texts from the sequence of numbers. The NMT was trained using two datasets; one is a Japanese-English parallel corpus containing 2.8 million pairs of sentences, which were extracted from TV and movie subtitles, while the other is a Japanese text dataset containing 32 million sentences, which were extracted from a question-and-answer platform. Using the model, phonemes and accent symbols were estimated from a sequence of numbers. Thus, the result accuracy in symbol levels was 91.48% and 43.45% of all the sentences were completely estimated with no errors. To subjectively evaluate feasibility of the NMT model, a two-person word association game was conducted; one gave hints using synthesized speech that is generated from symbols estimated by NMT, while the other guessed answers. As a result, 67.95% of all the quizzes were correctly answered, and experiment results show that the proposed method has the potential for dysarthria to communicate with TTS using a wearable keyboard.

DOI： 10.1109/APSIPAASC58517.2023.10317228

Speech-Emotion Control for Text-to-Speech in Spoken Dialogue Systems Using Voice Conversion and x-vector Embedding 査読国際誌

Shunichi Kohara, Masanobu Abe, Sunao Hara

2023 Asia Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC 2023) 2280 - 2286 2023年11月

記述言語：英語掲載種別：研究論文（国際会議プロシーディングス）

In this paper, we propose an algorithm to control both speaker individuality and emotional expressions in synthesized speech, where the most important feature is the controllability of intensity in emotional expressions. An aim of the proposed algorithm is to generate various responses including emotions in text-to-speech (TTS) for spoken dialogue systems (SDS), which results in making the system more human-like. An idea is to control emotion and its intensity in line with the user's utterances. For example, when a user happily talks to SDS, the agent of the SDS responses with happy voice. Generally, voice quality of a user and the agent are different. Therefore, the proposed algorithm consists of two steps: (1) voice conversion to change speaker individuality including emotional expressions and (2) TTS with x-vector acting as an embedding vector to mainly control speech quality related to the intensity of emotions. Evaluation experiments are carried out using a scenario of a spoken dialogue system, where a teacher system of TTS encourages or cheers up students according to students' utterances. The experiment results showed that TTS can successfully reproduce the emotion and its intensity that are extracted from students' utterances, while maintaining the teacher's speaker individuality.

DOI： 10.1109/APSIPAASC58517.2023.10317413

Sound map of urban areas recorded by smart devices: case study at Okayama and Kurashiki 招待国際誌

Sunao Hara, Masanobu Abe

Proceedings of the 52nd International Congress and Exposition on Noise Control Engineering (Inter-Noise 2023) 1 - 12 2023年8月

Predictions for sound events and soundscape impressions from environmental sound using deep neural networks 招待国際誌

Sunao Hara, Masanobu Abe

Proceedings of the 52nd International Congress and Exposition on Noise Control Engineering (Inter-Noise 2023) 1 - 12 2023年8月

Prediction method of Soundscape Impressions using Environmental Sounds and Aerial Photographs 査読国際誌

Yusuke Ono, Sunao Hara, Masanobu Abe

2022 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC) 1222 - 1227 2022年11月

Incremental Audio Scene Classifier Using Rehearsal-Based Strategy 査読国際誌

Ibnu Daqiqil Id, Masanobu Abe, Sunao Hara

2022 IEEE 10th Global Conference on Consumer Electronics (GCCE) 69 - 623 2022年10月

Speech-Like Emotional Sound Generation Using WaveNet 査読

Kento Matsumoto, Sunao Hara, Masanobu Abe

IEICE Transactions on Information and Systems E105.D ( 9 ) 1581 - 1589 2022年9月

記述言語：英語掲載種別：研究論文（学術雑誌）出版者・発行元：Institute of Electronics, Information and Communications Engineers (IEICE)

In this paper, we propose a new algorithm to generate Speech-like Emotional Sound (SES). Emotional expressions may be the most important factor in human communication, and speech is one of the most useful means of expressing emotions. Although speech generally conveys both emotional and linguistic information, we have undertaken the challenge of generating sounds that convey emotional information alone. We call the generated sounds "speech-like," because the sounds do not contain any linguistic information. SES can provide another way to generate emotional response in human-computer interaction systems. To generate "speech-like" sound, we propose employing WaveNet as a sound generator conditioned only by emotional IDs. This concept is quite different from the WaveNet Vocoder, which synthesizes speech using spectrum information as an auxiliary feature. The biggest advantage of our approach is that it reduces the amount of emotional speech data necessary for training by focusing on non-linguistic information. The proposed algorithm consists of two steps. In the first step, to generate a variety of spectrum patterns that resemble human speech as closely as possible, WaveNet is trained with auxiliary mel-spectrum parameters and Emotion ID using a large amount of neutral speech. In the second step, to generate emotional expressions, WaveNet is retrained with auxiliary Emotion ID only using a small amount of emotional speech. Experimental results reveal the following: (1) the two-step training is necessary to generate the SES with high quality, and (2) it is important that the training use a large neutral speech database and spectrum information in the first step to improve the emotional expression and naturalness of SES.

DOI： 10.1587/transinf.2021edp7236

その他リンク： https://www.webofscience.com/wos/woscc/full-record/WOS:000852731400008

Concept drift adaptation for audio scene classification using high-level features 査読国際誌

Ibnu Daqiqil Id, Masanobu Abe, Sunao Hara

2022 IEEE International Conference on Consumer Electronics (ICCE) 2022年1月

Acoustic Scene Classifier Based on Gaussian Mixture Model in the Concept Drift Situation 査読国際誌

Ibnu Daqiqil Id, Masanobu Abe, Sunao Hara

Advances in Science, Technology and Engineering Systems Journal 6 ( 5 ) 167 - 176 2021年9月

Phonetic and Prosodic Information Estimation from Texts for Genuine Japanese End-to-End Text-to-Speech 査読国際誌

Naoto Kakegawa, Sunao Hara, Masanobu Abe, Yusuke Ijima

Interspeech 2021 126 - 130 2021年8月

記述言語：英語掲載種別：研究論文（国際会議プロシーディングス）出版者・発行元：ISCA

The biggest obstacle to develop end-to-end Japanese text-to-speech (TTS) systems is to estimate phonetic and prosodic information (PPI) from Japanese texts. The following are the reasons: (1) the Kanji characters of the Japanese writing system have multiple corresponding pronunciations, (2) there is no separation mark between words, and (3) an accent nucleus must be assigned at appropriate positions. In this paper, we propose to solve the problems by neural machine translation (NMT) on the basis of encoder-decoder models, and compare NMT models of recurrent neural networks and the Transformer architecture. The proposed model handles texts on token (character) basis, although conventional systems handle them on word basis. To ensure the potential of the proposed approach, NMT models are trained using pairs of sentences and their PPIs that are generated by a conventional Japanese TTS system from 5 million sentences. Evaluation experiments were performed using PPIs that are manually annotated for 5,142 sentences. The experimental results showed that the Transformer architecture has the best performance, with 98.0% accuracy for phonetic information estimation and 95.0% accuracy for PPI estimation. Judging from the results, NMT models are promising toward end-to-end Japanese TTS.

DOI： 10.21437/interspeech.2021-914

Model architectures to extrapolate emotional expressions in DNN-based text-to-speech 査読国際誌

Katsuki Inoue, Sunao Hara, Masanobu Abe, Nobukatsu Hojo, Yusuke Ijima

Speech Communication 126 35 - 43 2021年2月

記述言語：英語掲載種別：研究論文（学術雑誌）出版者・発行元：Elsevier BV

This paper proposes architectures that facilitate the extrapolation of emotional expressions in deep neural network (DNN)-based text-to-speech (TTS). In this study, the meaning of “extrapolate emotional expressions” is to borrow emotional expressions from others, and the collection of emotional speech uttered by target speakers is unnecessary. Although a DNN has potential power to construct DNN-based TTS with emotional expressions and some DNN-based TTS systems have demonstrated satisfactory performances in the expression of the diversity of human speech, it is necessary and troublesome to collect emotional speech uttered by target speakers. To solve this issue, we propose architectures to separately train the speaker feature and the emotional feature and to synthesize speech with any combined quality of speakers and emotions. The architectures are parallel model (PM), serial model (SM), auxiliary input model (AIM), and hybrid models (PM&AIM and SM&AIM). These models are trained through emotional speech uttered by few speakers and neutral speech uttered by many speakers. Objective evaluations demonstrate that the performances in the open-emotion test provide insufficient information. They make a comparison with those in the closed-emotion test, but each speaker has their own manner of expressing emotion. However, subjective evaluation results indicate that the proposed models could convey emotional information to some extent. Notably, the PM can correctly convey sad and joyful emotions at a rate of 60%.

DOI： 10.1016/j.specom.2020.11.004

その他リンク： https://arxiv.org/abs/2102.10345

Module Comparison of Transformer-TTS for Speaker Adaptation based on Fine-tuning 査読国際誌

Katsuki Inoue, Sunao Hara, Masanobu Abe

Proceedings of APSIPA Annual Summit and Conference (APSIPA-ASC 2020) 826 - 830 2020年12月

記述言語：英語掲載種別：研究論文（国際会議プロシーディングス）出版者・発行元：IEEE/APSIPA

End-to-end text-to-speech (TTS) models have achieved remarkable results in recent times. However, the model requires a large amount of text and audio data for training. A speaker adaptation method based on fine-tuning has been proposed for constructing a TTS model using small scale data. Although these methods can replicate the target speaker s voice quality, synthesized speech includes the deletion and/or repetition of speech. The goal of speaker adaptation is to change the voice quality to match the target speaker ' s on the premise that adjusting the necessary modules will reduce the amount of data to be fine-tuned. In this paper, we clarify the role of each module in the Transformer-TTS process by not updating it. Specifically, we froze character embedding, encoder, layer predicting stop token, and loss function for estimating sentence ending. The experimental results showed the following: (1) fine-tuning the character embedding did not result in an improvement in the deletion and/or repetition of speech, (2) speech deletion increases if the encoder is not fine-tuned, (3) speech deletion was suppressed when the layer predicting stop token is not fine-tuned, and (4) there are frequent speech repetitions at sentence end when the loss function estimating sentence ending is omitted.

Concept Drift Adaptation for Acoustic Scene Classifier Based on Gaussian Mixture Model 査読

Ibnu Daqiqil Id, Masanobu Abe, Sunao Hara

Proceedings of IEEE REGION 10 CONFERENCE (TENCON 2020) 450 - 455 2020年11月

Controlling the Strength of Emotions in Speech-Like Emotional Sound Generated by WaveNet 査読国際誌

Kento Matsumoto, Sunao Hara, Masanobu Abe

Proceedings of Interspeech 2020 3421 - 3425 2020年10月

Semi-Supervised Speaker Adaptation for End-to-End Speech Synthesis with Pretrained Models 査読国際共著国際誌

Katsuki Inoue, Sunao Hara, Masanobu Abe, Tomoki Hayashi, Ryuichi Yamamoto, Shinji Watanabe

Proceedings of IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2020) 7634 - 7638 2020年5月

記述言語：英語掲載種別：研究論文（国際会議プロシーディングス）出版者・発行元：IEEE

Recently, end-to-end text-to-speech (TTS) models have achieved a remarkable performance, however, requiring a large amount of paired text and speech data for training. On the other hand, we can easily collect unpaired dozen minutes of speech recordings for a target speaker without corresponding text data. To make use of such accessible data, the proposed method leverages the recent great success of state-of-the-art end-to-end automatic speech recognition (ASR) systems and obtains corresponding transcriptions from pretrained ASR models. Although these models could only provide text output instead of intermediate linguistic features like phonemes, end-to-end TTS can be well trained with such raw text data directly. Thus, the proposed method can greatly simplify a speaker adaptation pipeline by consistently employing end-to-end ASR/TTS ecosystems. The experimental results show that our proposed method achieved comparable performance to a paired data adaptation method in terms of subjective speaker similarity and objective cepstral distance measures.

DOI： 10.1109/icassp40776.2020.9053371

DNN-based Voice Conversion with Auxiliary Phonemic Information to Improve Intelligibility of Glossectomy Patients' Speech 査読国際誌

Hiroki Murakami, Sunao Hara, Masanobu Abe

Proceedings of APSIPA Annual Summit and Conference 2019 138 - 142 2019年11月

Speech-like Emotional Sound Generator by WaveNet 査読国際誌

Kento Matsumoto, Sunao Hara, Masanobu Abe

Proceedings of APSIPA Annual Summit and Conference 2019 143 - 147 2019年11月

A signal processing perspective on human gait: Decoupling walking oscillations and gestures 査読国際誌

Adrien Gregorj, Zeynep Yücel, Sunao Hara, Akito Monden, Masahiro Shiomi

Proceedings of the 4th International Conference on Interactive Collaborative Robotics 2019 (ICR 2019) 11659 75 - 85 2019年8月

Naturalness Improvement Algorithm for Reconstructed Glossectomy Patient's Speech Using Spectral Differential Modification in Voice Conversion. 査読国際誌

Hiroki Murakami, Sunao Hara, Masanobu Abe, Masaaki Sato, Shogo Minagi

Interspeech 2018, 19th Annual Conference of the International Speech Communication Association, Hyderabad, India, 2-6 September 2018. 2464 - 2468 2018年9月

Sound sensing using smartphones as a crowdsourcing approach. 査読国際誌

Sunao Hara, Asako Hatakeyama, Shota Kobayashi, Masanobu Abe

2017 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2017, Kuala Lumpur, Malaysia, December 12-15, 2017 1328 - 1333 2017年12月

An investigation to transplant emotional expressions in DNN-based TTS synthesis. 査読国際誌

Katsuki Inoue, Sunao Hara, Masanobu Abe, Nobukatsu Hojo, Yusuke Ijima

2017 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2017, Kuala Lumpur, Malaysia, December 12-15, 2017 1253 - 1258 2017年12月

New monitoring scheme for persons with dementia through monitoring-area adaptation according to stage of disease. 査読国際誌

Shigeki Kamada, Yuji Matsuo, Sunao Hara, Masanobu Abe

Proceedings of the 1st ACM SIGSPATIAL Workshop on Recommendations for Location-based Services and Social Networks, LocalRec@SIGSPATIAL 2017, Redondo Beach, CA, USA, November 7-10, 2017 1:1 - 1:7 2017年11月

Prediction of subjective assessments for a noise map using deep neural networks. 査読国際誌

Shota Kobayashi, Masanobu Abe, Sunao Hara

Adjunct Proceedings of the 2017 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2017 ACM International Symposium on Wearable Computers, UbiComp/ISWC 2017, Maui, HI, USA, September 11-15, 2017 113 - 116 2017年9月

Speaker Dependent Approach for Enhancing a Glossectomy Patient’s Speech via GMM-Based Voice Conversion

Kei Tanaka, Sunao Hara, Masanobu Abe, Masaaki Sato, Shogo Minagi

Interspeech 2017 2017年8月

Speaker Dependent Approach for Enhancing a Glossectomy Patient's Speech via GMM-based Voice Conversion

Kei Tanaka, Sunao Hara, Masanobu Abe, Masaaki Sato, Shogo Minagi

18TH ANNUAL CONFERENCE OF THE INTERNATIONAL SPEECH COMMUNICATION ASSOCIATION (INTERSPEECH 2017), VOLS 1-6 3384 - 3388 2017年

記述言語：英語掲載種別：研究論文（国際会議プロシーディングス）出版者・発行元：ISCA-INT SPEECH COMMUNICATION ASSOC

In this paper, using GMM-based voice conversion algorithm, we propose to generate speaker-dependent mapping functions to improve the intelligibility of speech uttered by patients with a wide glossectomy. The speaker-dependent approach enables to generate the mapping functions that reconstruct missing spectrum features of speech uttered by a patient without having influences of a speaker's factor. The proposed idea is simple, i.e., to collect speech uttered by a patient before and after the glossectomy, but in practice it is hard to ask patients to utter speech just for developing algorithms. To confirm the performance of the proposed approach, in this paper, in order to simulate glossectomy patients, we fabricated an intraoral appliance which covers lower dental arch and tongue surface to restrain tongue movements. In terms of the Mel-frequency cepstrum (MFC) distance, by applying the voice conversion, the distances were reduced by 25% and 42% for speaker dependent case and speaker-independent case, respectively. In terms of phoneme intelligibility, dictation tests revealed that speech reconstructed by speaker-dependent approach almost always showed better performance than the original speech uttered by simulated patients, while speaker-independent approach did not.

DOI： 10.21437/Interspeech.2017-841

Enhancing a glossectomy patient's speech via GMM-based voice conversion 査読国際誌

Kei Tanaka, Sunao Hara, Masanobu Abe, Shogo Minagi

2016 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA) 1 - 4 2016年12月

LiBS: Lifelog browsing system to support sharing of memories 査読国際誌

Atsuya Namba, Sunao Hara, Masanobu Abe

UbiComp 2016 Adjunct - Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing 165 - 168 2016年9月

記述言語：英語掲載種別：研究論文（国際会議プロシーディングス）出版者・発行元：Association for Computing Machinery, Inc

We propose a lifelog browsing system through which users can share memories of their experiences with other users. Most importantly, by using global positioning system data and time stamps, the system simultaneously displays a variety of log information in a time-synchronous manner. This function empowers users with not only an easy interpretation of other users' experiences but also nonverbal notifications. Shared information on this system includes photographs taken by users, Google street views, shops and restaurants on the map, daily weather, and other items relevant to users' interests. In evaluation experiments, users preferred the proposed system to conventional photograph albums and maps for explaining and sharing their experiences. Moreover, through displayed information, the listeners found out their interest items that had not been mentioned by the speakers.

DOI： 10.1145/2968219.2971401

その他リンク： http://doi.acm.org/10.1145/2968219.2971401

Safety vs. Privacy: User preferences from the monitored and monitoring sides of a monitoring system 査読国際誌

Shigeki Kamada, Sunao Hara, Masanobu Abe

UbiComp 2016 Adjunct - Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing 101 - 104 2016年9月

記述言語：英語掲載種別：研究論文（国際会議プロシーディングス）出版者・発行元：Association for Computing Machinery, Inc

In this study, in order to develop a monitoring system that takes into account privacy issues, we investigated user preferences in terms of the monitoring and privacy protec-tion levels. The people on the monitoring side wanted the monitoring system to allow them to monitor in detail. Con-versely, it was observed for the people being monitored that the more detailed the monitoring, the greater the feelings of being surveilled intrusively. Evaluation experiments were performed using the location data of three people in differ-ent living areas. The results of the experiments show that it is possible to control the levels of monitoring and privacy protection without being affected by the shape of a living area by adjusting the quantization level of location informa-tion. Furthermore, it became clear that the granularity of location information satisfying the people on the monitored side and the monitoring side is different.

DOI： 10.1145/2968219.2971412

その他リンク： http://doi.acm.org/10.1145/2968219.2971412

Sound collection systems using a crowdsourcing approach to construct sound map based on subjective evaluation 査読国際誌

Sunao Hara, Shota Kobayashi, Masanobu Abe

IEEE ICME Workshop on Multimedia Mobile Cloud for Smart City Applications (MMCloudCity-2016) 1 - 6 2016年

担当区分：筆頭著者記述言語：英語掲載種別：研究論文（国際会議プロシーディングス）出版者・発行元：IEEE

This paper presents a sound collection system that uses crowdsourcing to gather information for visualizing area characteristics. First, we developed a sound collection system to simultaneously collect physical sounds, their statistics, and subjective evaluations. We then conducted a sound collection experiment using the developed system on 14 participants. We collected 693,582 samples of equivalent Aweighted loudness levels and their locations, and 5,935 samples of sounds and their locations. The data also include subjective evaluations by the participants. In addition, we analyzed the changes in sound properties of some areas before and after the opening of a large-scale shopping mall in a city. Next, we implemented visualizations on the server system to attract users' interests. Finally, we published the system, which can receive sounds from any Android smartphone user. The sound data were continuously collected and achieved a specified result.

DOI： 10.1109/ICMEW.2016.7574694

A Spoken Dialog System with Redundant Response to Prevent User Misunderstanding 査読国際誌

Masaki Yamaoka, Sunao Hara, Masanobu Abe

Proceedings of APSIPA Annual Summit and Conference 2015 229 - 232 2015年12月

記述言語：英語掲載種別：研究論文（国際会議プロシーディングス）出版者・発行元：IEEE

We propose a spoken dialog strategy for car navigation systems to facilitate safe driving. To drive safely, drivers need to concentrate on their driving; however, their concentration may be disrupted due to disagreement with their spoken dialog system. Therefore, we need to solve the problems of user misunderstandings as well as misunderstanding of spoken dialog systems. For this purpose, we introduced a driver workload level in spoken dialog management in order to prevent user misunderstandings. A key strategy of the dialog management is to make speech redundant if the driver's workload is too high in assuming that the user probably misunderstand the system utterance under such a condition. An experiment was conducted to compare performances of the proposed method and a conventional method using a user simulator. The simulator is developed under the assumption of two types of drivers: an experienced driver model and a novice driver model. Experimental results showed that the proposed strategies achieved better performance than the conventional one for task completion time, task completion rate, and user's positive speech rate. In particular, these performance differences are greater for novice users than for experienced users.

DOI： 10.1109/APSIPA.2015.7415511

Extracting Daily Patterns of Human Activity Using Non-Negative Matrix Factorization 査読国際誌

Masanobu Abe, Akihiko Hirayama, Sunao Hara

Proceedings of IEEE International Conference on Consumer Electronics (IEEE-ICCE 2015) 36 - 39 2015年1月

記述言語：英語掲載種別：研究論文（国際会議プロシーディングス）出版者・発行元：IEEE

This paper presents an algorithm to mine basic patterns of human activities on a daily basis using non-negative matrix factorization (NMF). The greatest benefit of the algorithm is that it can elicit patterns from which meanings can be easily interpreted. To confirm its performance, the proposed algorithm was applied to PC logging data collected from three occupations in offices. Daily patterns of software usage were extracted for each occupation. Results show that each occupation uses specific software in its own time period, and uses several types of software in parallel in its own combinations. Experiment results also show that patterns of 144 dimension vectors were compressible to those of 11 dimension vectors without degradation in occupation classification performance. Therefore, the proposed algorithm compressed basic software usage patterns to about one-tenth of their original dimensions while preserving the original information. Moreover, the extracted basic patterns showed reasonable interpretation of daily working patterns in offices.

DOI： 10.1109/ICCE.2015.7066309

Sound collection and visualization system enabled participatory and opportunistic sensing approaches 査読国際誌

Sunao Hara, Masanobu Abe, Noboru Sonehara

Proceedings of 2015 IEEE International Conference on Pervasive Computing and Communication Workshops (PerCom Workshops) 390 - 395 2015年

記述言語：英語掲載種別：研究論文（国際会議プロシーディングス）出版者・発行元：IEEE

This paper presents a sound collection system to visualize environmental sounds that are collected using a crowd sourcing approach. An analysis of physical features is generally used to analyze sound properties; however, human beings not only analyze but also emotionally connect to sounds. If we want to visualize the sounds according to the characteristics of the listener, we need to collect not only the raw sound, but also the subjective feelings associated with them. For this purpose, we developed a sound collection system using a crowdsourcing approach to collect physical sounds, their statistics, and subjective evaluations simultaneously. We then conducted a sound collection experiment using the developed system on ten participants. We collected 6,257 samples of equivalent loudness levels and their locations, and 516 samples of sounds and their locations. Subjective evaluations by the participants are also included in the data. Next, we tried to visualize the sound on a map. The loudness levels are visualized as a color map and the sounds are visualized as icons which indicate the sound type. Finally, we conducted a discrimination experiment on the sound to implement a function of automatic conversion from sounds to appropriate icons. The classifier is trained on the basis of the GMM-UBM (Gaussian Mixture Model and Universal Background Model) method. Experimental results show that the F-measure is 0.52 and the AUC is 0.79.

DOI： 10.1109/PERCOMW.2015.7134069

その他リンク： https://ousar.lib.okayama-u.ac.jp/ja/53271

Algorithm to Estimate a Living Area Based on Connectivity of Places with Home 査読国際誌

Yuji Matsuo, Sunao Hara, Masanobu Abe

HCI International 2015 - Posters’ Extended Abstracts (Part II), CCIS 529 529 570 - 576 2015年

記述言語：英語掲載種別：論文集(書籍)内論文出版者・発行元：SPRINGER-VERLAG BERLIN

We propose an algorithm to estimate a person's living area using his/her collected Global Positioning System (GPS) data. The most important feature of the algorithm is the connectivity of places with a home, i.e., a living area must consist of a home, important places, and routes that connect them. This definition is logical because people usually go to a place from home, and there can be several routes to that place. Experimental results show that the proposed algorithm can estimate living area with a precision of 0.82 and recall of 0.86 compared with the grand truth established by users. It is also confirmed that the connectivity of places with a home is necessary to estimate a reasonable living area.

DOI： 10.1007/978-3-319-21383-5_95

Extraction of Key Segments from Day-Long Sound Data 査読国際誌

Akinori Kasai, Sunao Hara, Masanobu Abe

HCI International 2015 - Posters’ Extended Abstracts (Part I), CCIS 528 528 620 - 626 2015年

記述言語：英語掲載種別：論文集(書籍)内論文出版者・発行元：SPRINGER-VERLAG BERLIN

We propose a method to extract particular sound segments from the sound recorded during the course of a day in order to provide sound segments that can be used to facilitate memory. To extract important parts of the sound data, the proposed method utilizes human behavior based on a multisensing approach. To evaluate the performance of the proposed method, we conducted experiments using sound, acceleration, and global positioning system data collected by five participants for approximately two weeks. The experimental results are summarized as follows: (1) various sounds can be extracted by dividing a day into scenes using the acceleration data; (2) sound recorded in unusual places is preferable to sound recorded in usual places; and (3) speech is preferable to nonspeech sound.

DOI： 10.1007/978-3-319-21380-4_105

Sub-Band Text-to-Speech Combining Sample-Based Spectrum with Statistically Generated Spectrum 査読国際誌

Tadashi Inai, Sunao Hara, Masanobu Abe, Yusuke Ijima, Noboru Miyazaki, Hideyuki Mizuno

Proceedings of Interspeech 2015 264 - 268 2015年

記述言語：英語掲載種別：研究論文（国際会議プロシーディングス）出版者・発行元：ISCA

As described in this paper, we propose a sub-band speech synthesis approach to develop a high quality Text-to-Speech (TTS) system: a sample-based spectrum is used in the high-frequency band and spectrum generated by HMM-based TTS is used in the low-frequency band. Herein, sample-based spectrum means spectrum selected from a phoneme database such that it is the most similar to spectrum generated by HMM-based speech synthesis. A key idea is to compensate over-smoothing caused by statistical procedures by introducing a sample-based spectrum, especially in the high-frequency band. Listening test results show that the proposed method has better performance than HMM-based speech synthesis in terms of clarity. It is at the same level as HMM-based speech synthesis in terms of smoothness. In addition, preference test results among the proposed method, HMM-based speech synthesis, and waveform speech synthesis using 80 min speech data reveal that the proposed method is the most liked.

その他リンク： http://dblp.uni-trier.de/db/conf/interspeech/interspeech2015.html#conf/interspeech/InaiHAIMM15

Inhibitory Effects of an Orally Active Small Molecule Alpha4beta1/Alpha4beta7 Integrin Antagonist, TRK-170, on Spontaneous Colitis in HLA-B27 Transgenic Rats

Hiroe Hirokawa, Yoko Koga, Rie Sasaki, Sunao Hara, Hiroyuki Meguro, Mie Kainoh

GASTROENTEROLOGY 146 ( 5 ) S640 - S640 2014年5月

A graph-based spoken dialog strategy utilizing multiple understanding hypotheses 査読

Norihide Kitaoka, Yuji Kinoshita, Sunao Hara, Chiyomi Miyajima, Kazuya Takeda

Information and Media Technologies 9 ( 1 ) 111 - 120 2014年3月

記述言語：英語掲載種別：研究論文（学術雑誌）出版者・発行元：Information and Media Technologies Editorial Board

We regarded a dialog strategy for information retrieval as a graph search problem and proposed several novel dialog strategies that can recover from misrecognition through a spoken dialog that traverses the graph. To recover from misrecognition without seeking confirmation, our system kept multiple understanding hypotheses at each turn and searched for a globally optimal hypothesis in the graph whose nodes express understanding states across user utterances in a whole dialog. In the search, we used a new criterion based on efficiency in information retrieval and consistency with understanding hypotheses, which is also used to select an appropriate system response. We showed that our system can make more efficient and natural dialogs than previous ones.

DOI： 10.11185/imt.9.111

New approach to emotional information exchange: Experience metaphor based on life logs 査読国際誌

Masanobu Abe, Daisuke Fujioka, Kazuto Hamano, Sunao Hara, Rika Mochizuki, Tomoki Watanabe

2014 IEEE International Conference on Pervasive Computing and Communication Workshops, PerCom 2014 Workshops 191 - 194 2014年3月

記述言語：英語掲載種別：研究論文（国際会議プロシーディングス）出版者・発行元：IEEE

We are striving to develop a new communication technology based on individual experiences that can be extracted from life logs. We have proposed the "Emotion Communication Model" and confirmed that significant correlation exists between experience and emotion. As the second step, particularly addressing impressive places and events, this paper describes an investigation of the extent to which we can share emotional information with others through individuals' experiences. Subjective experiments were conducted using life log data collected during 7-47 months. Experiment results show that (1) impressive places are determined by the distance from home, visit frequency, and direction from home and that (2) positive emotional information is highly consistent among people (71.4%), but it is not true for negative emotional information. Therefore, experiences are useful as metaphors to express positive emotional information.

DOI： 10.1109/PerComW.2014.6815198

Development of a Toolkit Handling Multiple Speech-Oriented Guidance Agents for Mobile Applications 査読国際誌

Sunao Hara, Hiromichi Kawanami, Hiroshi Saruwatari, Kiyohiro Shikano

Natural Interaction with Robots, Knowbots and Smartphones, Putting Spoken Dialog Systems into Practice 79 - 85 2014年

Evaluation of Invalid Input Discrimination Using Bag-of-Words for Speech-Oriented Guidance System 査読国際誌

Haruka Majima, Rafael Torres, Hiromichi Kawanami, Sunao Hara, Tomoko Matsui, Hiroshi Saruwatari, Kiyohiro Shikano

Natural Interaction with Robots, Knowbots and Smartphones, Putting Spoken Dialog Systems into Practice 389 - 397 2014年

A Hybrid Text-to-Speech Based on Sub-Band Approach 査読国際誌

Takuma Inoue, Sunao Hara, Masanobu Abe

Proceedings of Asia-Pacific Signal and Information Processing Association 2014 Annual Summit and Conference 1 - 4 2014年

記述言語：英語掲載種別：研究論文（国際会議プロシーディングス）出版者・発行元：IEEE

This paper proposes a sub-band speech synthesis approach to develop high-quality Text-to-Speech (TTS). For the low-frequency band and high-frequency band, Hidden Markov Model (HMM)-based speech synthesis and waveform -based speech synthesis are used, respectively. Both speech synthesis methods are widely known to show good performance and to have benefits and shortcomings from different points of view. One motivation is to apply the right speech synthesis method in the right frequency band. Experiment results show that in terms of the smoothness the proposed approach shows better performance than waveform -based speech synthesis, and in terms of the clarity it shows better than HMM-based speech synthesis. Consequently, the proposed approach combines the inherent benefits from both waveform-based speech synthesis and HMM-based speech synthesis.

DOI： 10.1109/APSIPA.2014.7041575

音声情報案内システムにおけるBag-of-Wordsを用いた無効入力の棄却査読

真嶋温佳, 藤田洋子, トーレス・ラファエル, 川波弘道, 原直, 松井知子, 猿渡洋, 鹿野清宏

情報処理学会論文誌 54 ( 2 ) 443 - 451 2013年2月

記述言語：日本語出版者・発行元：情報処理学会

実環境における音声認識を用いた情報案内システムでは，雑音等の非音声やユーザ同士の背景会話など，システムへの入力として不適切な入力が存在する．これらの入力はシステムの誤作動・誤認識の原因となるので，システムへの入力として適切な入力（有効入力）と不適切な入力（無効入力）の識別を行い，無効入力を棄却することにより，無効入力に対する応答処理を行わないことが重要である．従来，有効入力と無効入力との識別には，メル周波数ケプストラム係数などの音響的特徴量によるGMM（Gaussian Mixture Model）が用いられる．しかし，入力データの音声認識結果から得られる言語的な情報を使うことにより，システムのタスクを考えたうえで有効入力と無効入力の識別が可能になると考えられる．そこで本論文では，音響特徴量にBag-of-Words（BOW）を言語的特徴量として併用した無効入力の識別を検討した．識別手法としては，サポートベクタマシン（SVM）および最大エントロピー法を用いた．実験には実環境音声情報案内システム「たけまるくん」の入力データを用いた．SVMによる識別結果では，GMMによる音響尤度のみを用いた場合に比べて，BOWを用いた場合，F尺度を82.19%から85.41%に改善することができた．さらに，GMMによる音響尤度，発話時間，SNRを組み合わせた特徴量にBOWを追加することで，F尺度を86.58%まで改善することができた．詳細な分析の結果，BOWは特に無効入力の誤受理を減らす効果があることが示された．On a real environment speech-oriented information guidance system, a valid and invalid input discrimination is important as invalid inputs such as noise, laugh, cough and utterances between users lead to unpredictable system responses. Generally, acoustic features such as MFCC (Mel-Frequency Cepstral Coefficient) are used for discrimination. Comparing acoustic likelihoods of GMMs (Gaussian Mixture Models) from speech data and noise data is one of the typical methods. In addition to that, using linguistic features, such as speech recognition result, is considered to improve discrimination accuracy as it reflects the task-domain of invalid inputs and meaningless recognition results from noise inputs. In this paper, we introduce Bag-of-Words (BOW) as a feature to discriminate between valid and invalid inputs. Support Vector Machine (SVM) and Maximum Entropy method (ME) are also employed to realize robust classification. We experimented the methods using real environment data obtained from the guidance system "Takemaru-kun." By applying BOW on SVM, the F-measure is improved to 85.09%, from 82.19% when using GMMs. In addition, experiments using features combining BOW with acoustic likelihoods from GMMs, Duration and SNR were conducted, improving the F-measure to 86.58%.

音声対話システムの発話・動作タグN-gramを用いた課題未達成のオンライン検出査読

原直, 北岡教英, 武田一哉

電子情報通信学会論文誌 (D) J96-D ( 1 ) 81 - 93 2013年1月

担当区分：筆頭著者記述言語：日本語出版者・発行元：一般社団法人電子情報通信学会

本論文ではN-gram特徴を用いた音声対話システム利用時の課題未達成対話の検出手法を提案する.実験にはユーザが自分のPC上で利用するという,実環境下で収録された楽曲検索のための音声対話システムとの対話データを利用する.楽曲検索課題を行っている全ての対話データはユーザとシステムの発話を抽象化した発話・動作ダグにより記述し,そのタグ系列をN-gramとしてモデル化を行う.本研究では,タグ系列中のタグN-gramの出現回数を素性として,Support Vector MachineやC4.5決定木などの識別的手法による課題未達成対話の検出実験を行った.更に対話長や反応時間などの対話の特徴を表す対話変数を導入することで検出性能の向上を行った.その結果,ユーザの4回目の発話までを用いることで,約76%の識別率となった.

その他リンク： http://search.ieice.org/bin/summary.php?id=j96-d_1_81&category=D&year=2013&lang=J&abst=

Acoustic Model Training Using Pseudo-Speaker Features Generated by MLLR Transformations for Robust Speaker-Independent Speech Recognition 査読

Arata Itoh, Sunao Hara, Norihide Kitaoka, Kazuya Takeda

IEICE TRANSACTIONS on Information and Systems E95D ( 10 ) 2479 - 2485 2012年10月

記述言語：英語掲載種別：研究論文（学術雑誌）出版者・発行元：IEICE-INST ELECTRONICS INFORMATION COMMUNICATIONS ENG

A novel speech feature generation-based acoustic model training method for robust speaker-independent speech recognition is proposed. For decades, speaker adaptation methods have been widely used. All of these adaptation methods need adaptation data. However, our proposed method aims to create speaker-independent acoustic models that cover not only known but also unknown speakers. We achieve this by adopting inverse maximum likelihood linear regression (MLLR) transformation-based feature generation, and then we train our models using these features. First we obtain MLLR transformation matrices from a limited number of existing speakers. Then we extract the bases of the MLLR transformation matrices using PCA. The distribution of the weight parameters to express the transformation matrices for the existing speakers are estimated. Next, we construct pseudo-speaker transformations by sampling the weight parameters from the distribution, and apply the transformation to the normalized features of the existing speaker to generate the features of the pseudo-speakers. Finally, using these features, we train the acoustic models. Evaluation results show that the acoustic models trained using our proposed method are robust for unknown speakers.

DOI： 10.1587/transinf.E95.D.2479

その他リンク： http://search.ieice.org/bin/summary.php?id=e95-d_10_2479

Causal analysis of task completion errors in spoken music retrieval interactions 査読国際誌

Sunao Hara, Norihide Kitaoka, Kazuya Takeda

Proceedings of the 8th international conference on Language Resources and Evaluation (LREC 2012) 1365 - 1372 2012年5月

担当区分：筆頭著者記述言語：英語掲載種別：研究論文（国際会議プロシーディングス）出版者・発行元：EUROPEAN LANGUAGE RESOURCES ASSOC-ELRA

In this paper, we analyze the causes of task completion errors in spoken dialog systems, using a decision tree with N-gram features of the dialog to detect task-incomplete dialogs. The dialog for a music retrieval task is described by a sequence of tags related to user and system utterances and behaviors. The dialogs are manually classified into two classes: completed and uncompleted music retrieval tasks. Differences in tag classification performance between the two classes are discussed. We then construct decision trees which can detect if a dialog finished with the task completed or not, using information gain criterion. Decision trees using N-grams of manual tags and automatic tags achieved 74.2% and 80.4% classification accuracy, respectively, while the tree using interaction parameters achieved an accuracy rate of 65.7%. We also discuss more details of the causality of task incompletion for spoken dialog systems using such trees.

その他リンク： http://www.lrec-conf.org/proceedings/lrec2012/summaries/1059.html

Robust seed model training for speaker adaptation using pseudo-speaker features generated by inverse CMLLR transformation 査読国際誌

Arata Itoh, Sunao Hara, Norihide Kitaoka, Kazuya Takeda

Proceedings of 2011 Automatic Speech Recognition and Understanding Workshop (ASRU 2011) 169 - 172 2011年12月

記述言語：英語掲載種別：研究論文（国際会議プロシーディングス）出版者・発行元：IEEE

In this paper, we propose a novel acoustic model training method which is suitable for speaker adaptation in speech recognition. Our method is based on feature generation from a small amount of speakers' data. For decades, speaker adaptation methods have been widely used. Such adaptation methods need some amount of adaptation data and if the data is not sufficient, speech recognition performance degrade significantly. If the seed models to be adapted to a specific speaker can widely cover more speakers, speaker adaptation can perform robustly. To make such robust seed models, we adopt inverse maximum likelihood linear regression (MLLR) transformation-based feature generation, and then train our seed models using these features. First we obtain MLLR transformation matrices from a limited number of existing speakers. Then we extract the bases of the MLLR transformation matrices using PCA. The distribution of the weight parameters to express the MLLR transformation matrices for the existing speakers is estimated. Next we generate pseudo-speaker MLLR transformations by sampling the weight parameters from the distribution, and apply the inverse of the transformation to the normalized existing speaker features to generate the pseudo-speakers' features. Finally, using these features, we train the acoustic seed models. Using this seed models, we obtained better speaker adaptation results than using simply environmentally adapted models. © 2011 IEEE.

DOI： 10.1109/ASRU.2011.6163925

Training Robust Acoustic Models Using Features of Pseudo-Speakers Generated by Inverse CMLLR Transformations 査読国際誌

Arata Itoh, Sunao Hara, Norihide Kitaoka, Kazuya Takeda

Proceedings of 2011 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC 2011) 1 - 5 2011年12月

記述言語：英語掲載種別：研究論文（国際会議プロシーディングス）出版者・発行元：APSIPA

In this paper a novel speech feature generationbased acoustic model training method is proposed. For decades, speaker adaptation methods have been widely used. All existing adaptation methods need adaptation data. However, our proposed method creates speaker-independent acoustic models that cover not only known but also unknown speakers. We do this by adopting inverse maximum likelihood linear regression (MLLR) transformation-based feature generation, and then train our models using these features. First we obtain MLLR transformation matrices from a limited number of existing speakers. Then we extract the bases of the MLLR transformation matrices using PCA. The distribution of the weight parameters to express the MLLR transformation matrices for the existing speakers are estimated. Next we generate pseudo-speaker MLLR transformations by sampling the weight parameters from the distribution, and apply the inverse of the transformation to the normalized existing speaker features to generate the pseudospeakers' features. Finally, using these features, we train the acoustic models. Evaluation results show that the acoustic models which are created are robust for unknown speakers.

On-line detection of task incompletion for spoken dialog systems using utterance and behavior tag N-gram vectors 査読国際誌

Sunao Hara, Norihide Kitaoka, Kazuya Takeda

Proceedings of the Paralinguistic Information and Its Integration in Spoken Dialogue Systems Workshop 215 - 225 2011年9月

Detection of task-incomplete dialogs based on utterance-and-behavior tag N-gram for spoken dialog systems 査読国際誌

Sunao Hara, Norihide Kitaoka, Kazuya Takeda

Proceedings of INTERSPEECH 2011 1312 - 1315 2011年

担当区分：筆頭著者記述言語：英語掲載種別：研究論文（国際会議プロシーディングス）出版者・発行元：ISCA-INT SPEECH COMMUNICATION ASSOC

We propose a method of detecting "task incomplete" dialogs in spoken dialog systems using N-gram-based dialog models. We used a database created during a field test in which inexperienced users used a client-server music retrieval system with a spoken dialog interface on their own PCs. In this study, the dialog for a music retrieval task consisted of a sequence of user and system tags that related their utterances and behaviors. The dialogs were manually classified into two classes: the dialog either completed the music retrieval task or it didn't. We then detected dialogs that did not complete the task, using N-gram probability models or a Support Vector Machine with N-gram feature vectors trained using manually classified dialogs. Off-line and on-line detection experiments were conducted on a large amount of real data, and the results show that our proposed method achieved good classification performance.

その他リンク： http://www.isca-speech.org/archive/interspeech_2011/i11_1305.html

Music Recommendation System Based on Human-to-human Conversation Recognition 査読国際誌

Hiromasa Ohashi, Sunao Hara, Norihide Kitaoka, Kazuya Takeda

Workshop Proceedings of the 7th International Conference on Intelligent Environments: Ambient Intelligence and Smart Environments 10 352 - 361 2011年

記述言語：英語掲載種別：論文集(書籍)内論文出版者・発行元：IOS PRESS

We developed an ambient system that plays music suitable for the mood of a human-human conversation using words obtained from a continuous-speech recognition system. Using the correspondence between a document space based on the texts related to the music and an acoustic space that expresses various audio features, the continuous-speech recognition results are mapped to an acoustic space. We performed a subjective evaluation of the system. The subjects rated the recommended music and the result reveals that the 10 most highly recommended selections included suitable music.

DOI： 10.3233/978-1-60750-795-6-352

Automatic detection of task-incompleted dialog for spoken dialog system based on dialog act N-gram 査読国際誌

Sunao Hara, Norihide Kitaoka, Kazuya Takeda

Proceedings of INTERSPEECH2010 3034 - 3037 2010年9月

担当区分：筆頭著者記述言語：英語掲載種別：研究論文（国際会議プロシーディングス）出版者・発行元：ISCA

In this paper, we propose a method of detecting task-incompleted users for a spoken dialog system using an N-gram-based dialog history model. We collected a large amount of spoken dialog data accompanied by usability evaluation scores by users in real environments. The database was made by a field test in which naive users used a client-server music retrieval system with a spoken dialog interface on their own PCs. An N-gram model was trained from sequences that consist of user dialog acts and/or system dialog acts for two dialog classes, that is, the dialog completed the music retrieval task or the dialog incompleted the task. Then the system detects unknown dialogs that is not completed the task based on the N-gram likelihood. Experiments were conducted on large real data, and the results show that our proposed method achieved good classification performance. When the classifier correctly detected all of the task-incompleted dialogs, our proposed method achieved a false detection rate of 6%.

その他リンク： http://www.isca-speech.org/archive/interspeech_2010/i10_3034.html

Rapid acoustic model adaptation using inverse MLLR-based feature generation 査読国際誌

Arata Ito, Sunao Hara, Norihide Kitaoka, Kazuya Takeda

Proceedings of ICA2010 5 1 - 6 2010年8月

Estimation method of user satisfaction using N-gram-based dialog history model for spoken dialog system 査読国際誌

Sunao Hara, Norihide Kitaoka, Kazuya Takeda

LREC 2010 - SEVENTH INTERNATIONAL CONFERENCE ON LANGUAGE RESOURCES AND EVALUATION 78 - 83 2010年5月

担当区分：筆頭著者記述言語：英語掲載種別：研究論文（国際会議プロシーディングス）出版者・発行元：EUROPEAN LANGUAGE RESOURCES ASSOC-ELRA

In this paper, we propose an estimation method of user satisfaction for a spoken dialog system using an N-gram-based dialog history model. We have collected a large amount of spoken dialog data accompanied by usability evaluation scores by users in real environments. The database is made by a field-test in which naive users used a client-server music retrieval system with a spoken dialog interface on their own PCs. An N-gram model is trained from the sequences that consist of users' dialog acts and/or the system's dialog acts for each one of six user satisfaction levels: from 1 to 5 and phi (task not completed). Then, the satisfaction level is estimated based on the N-gram likelihood. Experiments were conducted on the large real data and the results show that our proposed method achieved good classification performance; the classification accuracy was 94.7% in the experiment on a classification into dialogs with task completion and those without task completion. Even if the classifier detected all of the task incomplete dialog correctly, our proposed method achieved the false detection rate of only 6%.

その他リンク： http://www.lrec-conf.org/proceedings/lrec2010/summaries/579.html

Data collection and usability study of a PC-based speech application in various user environments 査読国際誌

Sunao Hara, Chiyomi Miyajima, Katsunobu Ito, Norihide Kitaoka, Kazuya Takeda

Proceedings of Oriental-COCOSDA 2008 39 - 44 2008年11月

In-car Speech Data Collection along with Various Multimodal Signals 査読国際誌

Akira Ozaki, Sunao Hara, Takashi Kusakawa, Chiyomi Miyajima, Takanori Nishino, Norihide Kitaoka, Katunobu Itou, Kazuya Takeda

Proceedings of the Sixth International Conference on Language Resources and Evaluation (LREC'08) 1846 - 1851 2008年5月

記述言語：英語掲載種別：研究論文（国際会議プロシーディングス）出版者・発行元：EUROPEAN LANGUAGE RESOURCES ASSOC-ELRA

In this paper, a large-scale real-world speech database is introduced along with other multimedia driving data. We designed a data collection vehicle equipped with various sensors to synchronously record twelve-channel speech, three-channel video, driving behavior including gas and brake pedal pressures, steering angles, and vehicle velocities, physiological signals including driver heart rate, skin conductance, and emotion-based sweating on the palms and soles, etc. These multimodal data are collected while driving on city streets and expressways under four different driving task conditions including two kinds of monologues, human-human dialog, and human-machine dialog. We investigated the response timing of drivers against navigator utterances and found that most overlapped with the preceding utterance due to the task characteristics and the features of Japanese. When comparing utterance length, speaking rate, and the filler rate of driver utterances in human-human and human-machine dialogs, we found that drivers tended to use longer and faster utterances with more fillers to talk with humans than machines.

その他リンク： http://www.lrec-conf.org/proceedings/lrec2008/summaries/472.html

多様な音響環境下における音声認識システム利用時のデータ収集システム査読

原直, 宮島千代美, 伊藤克亘, 武田一哉

電子情報通信学会論文誌(D) J90-D ( 10 ) 2807 - 2816 2007年10月

担当区分：筆頭著者記述言語：日本語掲載種別：研究論文（学術雑誌）出版者・発行元：一般社団法人電子情報通信学会

多様なPC利用環境において音声認識の被験者実験を行うために,WWWを利用した音声対話システム及びそのデータ収集システムを構築した.本システムのユーザはPC上にインストールされたクライアントプログラムを用いることで音声対話によりPC内に蓄積された音楽を再生したり,音楽ダウンロードサイトの楽曲を試聴することができる.クライアントプログラムの利用により収集された音声データや対話ログはインターネットを介してサーバ上に蓄積される.サーバには,ユーザごとの辞書のカスタマイズ等の機能も実装している.本システムをインターネット上で試験的に公開し,2か月間のフィールドテストとしてデータ収集を行ったところ合計59時間のシステム稼動時データを収集した.そのうち約5時間41分のデータ(11351個)が音声区間として検出されており,システムに対して発話されていた音声データとして6335発話を得た.

An online customizable music retrieval system with a spoken dialogue interface 査読国際誌

Sunao Hara, Chiyomi Miyajima, Katsunobu Itou, Kazuya Takeda

The Journal of the Acoustical Society of America 120 ( 5-2 ) 3378 - 3379 2006年11月

Novel orally active alpha 4 integrin antagonist, T-728, attenuates dextran sodium sulfate-induced chronic colitis in mice

Ken-Ichi Hayashi, Hiroyuki Meguro, Sunao Hara, Rie Sasaki, Yoko Koga, Meiko Takeshita, Naoyoshi Yamamoto, Hiroe Hirokawa, Mie Kainoh

GASTROENTEROLOGY 130 ( 4 ) A352 - A352 2006年4月

Preliminary Study of a Learning Effect on Users to Develop a New Evaluation of the Spoken Dialogue System 査読国際誌

Sunao Hara, Ayako Shirose, Chiyomi Miyajima, Katsunobu Ito, Kazuya Takeda

Proceedings of Oriental-COCOSDA 2005 164 - 168 2005年12月

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