In-home detection of distress calls: the case of aged users

International audienceIn the context of technologies development aiming at helping aged people to live independently at home, the CIRDO1 project aims at implementing an ASR system into a social inclusion product designed for elderly people in order to detect distress situations and provide capability to call for help. In this context we present a system able to detect distress and call for help sentences on line

Speech-centric multimodal interaction for easy-to-access online services: A personal life assistant for the elderly

The PaeLife project is a European industry-academia collaboration whose goal is to provide the elderly with easy access to online services that make their life easier and encourage their continued participation in the society. To reach this goal, the project partners are developing a multimodal virtual personal life assistant (PLA) offering a wide range of services from weather information to social networking. This paper presents the multimodal architecture of the PLA, the services provided by the PLA, and the work done in the area of speech input and output modalities, which play a key role in the application.info:eu-repo/semantics/publishedVersio

Speech-centric multimodal interaction for easy-to-access online services: A personal life assistant for the elderly

The PaeLife project is a European industry-academia collaboration whose goal is to provide the elderly with easy access to online services that make their life easier and encourage their continued participation in the society. To reach this goal, the project partners are developing a multimodal virtual personal life assistant (PLA) offering a wide range of services from weather information to social networking. This paper presents the multimodal architecture of the PLA, the services provided by the PLA, and the work done in the area of speech input and output modalities, which play a key role in the application.info:eu-repo/semantics/publishedVersio

Contribution à l'étude de la variabilité de la voix des personnes âgées en reconnaissance automatique de la parole (Contribution to the study of elderly people's voice variability in automatic speech recognition) [in French]

National audienceL'utilisation de la reconnaissance vocale pour l'assistance à la vie autonome se heurte à la difficulté d'utilisation des systèmes de RAP qui ne sont pas prévus à la base pour la voix âgée. Pour caractériser les différences de comportement d'un système de reconnaissance entre les personnes âgées et non-âgées, nous avons étudié quels sont les phonèmes les moins bien reconnus en nous basant sur le corpus AD80 que nous avons enregistré. Les résultats montrent que certains phonèmes tels que les plosives sont plus spécifiquement affectés par l'âge. De plus nous avons recueilli le corpus spécifique ERES38 afin d'adapter les modèles acoustiques, avec pour résultat une diminution du taux d'erreur de mot de 15%. Malgré la grande variabilité des performances, nous avons caractérisé comment la baisse des performances du système de reconnaissance automatique de la parole peut être corrélée avec la baisse d'autonomie des personnes âgées

Speech-based interaction in an AAL context

International audiencePURPOSE The number of older persons in industrialized countries is steadily increasing. Seniors living alone are more numerous, and we must find solutions that will allow them to continue to stay at home comfortably and safely. Smart housings can be one of these solutions. One of the biggest challenges in ambient assisted living (AAL) is to develop smart homes that anticipate and respond to the needs of the inhabitants. Given the diverse profiles of the older adult population, it will therefore be essential to facilitate interaction with the smart home through systems that respond naturally to voice commands rather than using tactile interfaces. METHOD The first step in our study was to evaluate how well ambient assistive speech technology is received by the target population. We report on a user evaluation assessing acceptance and fear of this new technology. The experiment aimed at testing three important aspects of speech interaction: voice command, communication with the outside world, home automation system interrupting a person's activity. Participants were 7 older persons (71-88 years old), 7 relatives and 3 professional carers; the experiments were conducted in a smart home with a voice command using a Wizard-of-Oz technique. The second step in our study was related to the adaptation of speech recognition technologies to the older adult population. Judging by the literature this has not been extensively studied. In fact, it is known that industrialized speech recognition system models are not adapted to seniors but to other categories of the population. In order to do this we recorded a specific speech corpus (voice-age) with 7 older adults (70 to 89 years old) reading sentences (a total of 4 hours of speech). A second corpus (ERES38) of free talking (18 hours of speech) was recorded by 23 speakers (68-98 years old). These corpora were analyzed in a semi-automatic manner to reveal the aged-voice characteristics. RESULTS AND DISCUSSION Regarding the technical aspect, it appears that some phonemes are more affected by age than others. Thus, a specific adaptation of the acoustic models for ASR is required. Regarding the acceptance aspect, voice interfaces appear to have a great potential to ease daily living for older adults and frail persons and would be better accepted than other, more intrusive, solutions. By considering still healthy and independent older persons in the user evaluation, one interesting finding was overall acceptance provided the system is not conducive to a lazy lifestyle by taking control of everything. This particular concern must be addressed in the development of smart homes that support daily living by stressing the ability to control the daily routine rather than altering it. This study shows the great interest of voice interfaces to develop efficient solution to enable the growing number of older persons to continue to live in their own homes as long as possible

Multilingual speech recognition for the elderly: The AALFred personal life assistant

The PaeLife project is a European industry-academia collaboration in the framework of the Ambient Assisted Living Joint Programme (AAL JP), with a goal of developing a multimodal, multilingual virtual personal life assistant to help senior citizens remain active and socially integrated. Speech is one of the key interaction modalities of AALFred, the Windows application developed in the project; the application can be controlled using speech input in four European languages: French, Hungarian, Polish and Portuguese. This paper briefly presents the personal life assistant and then focuses on the speech-related achievements of the project. These include the collection, transcription and annotation of large corpora of elderly speech, the development of automatic speech recognisers optimised for elderly speakers, a speech modality component that can easily be reused in other applications, and an automatic grammar translation service that allows for fast expansion of the automatic speech recognition functionality to new languages.info:eu-repo/semantics/publishedVersio

Development of Automatic Speech Recognition Techniques for Elderly Home Support: Applications and Challenges

International audienceVocal command may have considerable advantages in terms of usability in the AAL domain. However, efficient audio analysis in smart home environment is a challenging task in large part because of bad speech recognition results in the case of elderly people. Dedicated speech corpora were recorded and employed to adapted generic speech recog-nizers to this type of population. Evaluation results of a first experiment allowed to draw conclusions about the distress call detection. A second experiments involved participants who played fall scenarios in a realistic smart home, 67% of the distress calls were detected online. These results show the difficulty of the task and serve as basis to discuss the stakes and the challenges of this promising technology for AAL

Speech Recognition of Aged Voices in the AAL Context: Detection of Distress Sentences

International audienceBy 2050, about a third of the French population will be over 65. In the context of technologies development aiming at helping aged people to live independently at home, the CIRDO project aims at implementing an ASR system into a social inclusion product designed for elderly people in order to detect distress situations. Speech recognition systems present higher word error rate when speech is uttered by elderly speakers compared to when non-aged voice is considered. Two specialized corpora in French, AD80 and ERES38, were recorded in this framework by aged people, they were used first to study the possibility of adaptation of standard ASR to aged voice. Then we looked at whether the variability of the WER between speakers could be correlated with the level of dependence. Then, we assessed the performance of distress sentence detection by a filter and we demonstrated a significant drop in performance for those with the lowest degree of autonomy

Construction of a corpus of elderly Japanese speech for analysis and recognition

Tokushima UniversityAichi Prefectural UniversityUniversity of YamanashiLREC 2018 Special Speech Sessions "Speech Resources Collection in Real-World Situations"; Phoenix Seagaia Conference Center, Miyazaki; 2018-05-09We have constructed a new speech data corpus using the utterances of 100 elderly Japanese people, in order to improve the accuracy of automatic recognition of the speech of older people. Humanoid robots are being developed for use in elder care nursing facilities because interaction with such robots is expected to help clients maintain their cognitive abilities, as well as provide them with companionship. In order for these robots to interact with the elderly through spoken dialogue, a high performance speech recognition system for the speech of elderly people is needed. To develop such a system, we recorded speech uttered by 100 elderly Japanese who had an average age of 77.2, most of them living in nursing homes. Another corpus of elderly Japanese speech called S-JNAS (Seniors-Japanese Newspaper Article Sentences) has been developed previously, but the average age of the participants was 67.6. Since the target age for nursing home care is around 75, much higher than that of most of the S-JNAS samples, we felt a more representative corpus was needed. In this study we compare the performance of our new corpus with both the Japanese read speech corpus JNAS (Japanese Newspaper Article Speech), which consists of adult speech, and with the S-JNAS, the senior version of JNAS, by conducting speech recognition experiments. Data from the JNAS, S-JNAS and CSJ (Corpus of Spontaneous Japanese) was used as training data for the acoustic models, respectively. We then used our new corpus to adapt the acoustic models to elderly speech, but we were unable to achieve sufficient performance when attempting to recognize elderly speech. Based on our experimental results, we believe that development of a corpus of spontaneous elderly speech and/or special acoustic adaptation methods will likely be necessary to improve the recognition performance of dialog systems for the elderly