How affects can perturbe the automatic speech recognition of domotic interactions

International audienceIn Smart Home, the vocal home automation orders, for comfort purposes, or assistive devoted, have been pointed as the more relevant interaction for ambient assisted living. Even if the orders are very strictly formulated, when they are daily used (directed to the smart home, or to a robot mediator), they become often pronounced with various affects. In this paper we have evaluated how some state of the art ASR systems shut down with expressive orders, acted or spontaneous, and how the ASR training with neutral and/or acted and/or spontaneous expressive commands corpus can greatly modify the ASR performances

Robustesse de la RAP à la parole expressive âgée vs. typique : contexte de commandes dans un habitat intelligent

International audienceLa commande vocale a été identifiée comme un mode d’interaction très intéressant dans l’habitat intelligent, qu’elle soit adressée directement à l’habitat ou à une interface robotique, aussi bien en ce qui concerne le confort que dans le domaine de l’assistance aux personnes âgées. Cependant, même lorsque le sujet peut contrôler sa production pour respecter strictement une référence imposée, dans le contexte naturel de l’usage quotidien « naturel » les productions vocales sont inévitablement souvent expressives. Dans cet article, à partir d’un corpus de parole émue actée/neutre collecté par élicitation,nous observons une chute significative de performance d’un système de RAP générique pour la parole émue par rapport à la voix neutre et nous évaluons le gain intéressant apporté par une adaptation du système. Nous concluons sur la nécessité de prendre en compte cette adaptationdans le développement d’un système vocal destiné à l’assistance aux personnes

Analysing the Performance of Automatic Speech Recognition for Ageing Voice: Does it Correlate with Dependency Level?

International audienceAmbient Assisted Living aims at providing assistance by allowing people with special needs to perform tasks which they have increasing difficulty with and to provide reassurance through surveillance in order to detect distress and accidental falls. Aged people are among the ones who might benefit from advances in ICT to live as long as possible in their own home. Voice-base smart home is a promising way to provide AAL, but even mature technologies must be evaluated from the perspec- tive of its potential beneficiaries. In this paper, we investigate which characteristics of the ageing voice that challenge a state of the art ASR system. Though in the literature, chronological age is retain as the sole factor predicting decrease in performance, we show that degree of loss of autonomy is even more correlated to ASR performance

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

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

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

Recognition of Distress Calls in Distant Speech Setting: a Preliminary Experiment in a Smart Home

International audienceThis paper presents a system to recognize distress speech in the home of seniors to provide reassurance and assistance. The system is aiming at being integrated into a larger system for Ambient Assisted Living (AAL) using only one microphone with a fix position in a non-intimate room. The paper presents the details of the automatic speech recognition system which must work under distant speech condition and with expressive speech. Moreover, privacy is ensured by running the decoding on-site and not on a remote server. Furthermore the system was biased to recognize only set of sentences defined after a user study. The system has been evaluated in a smart space reproducing a typical living room where 17 participants played scenarios including falls during which they uttered distress calls. The results showed a promising error rate of 29% while emphasizing the challenges of the task

Acquisition et reconnaissance automatique d'expressions et d'appels vocaux dans un habitat

International audienceThis paper presents a system to recognize calls for help in the home of seniors to provide reassurance and assistance. The system is using an ASR which must operate with distant and expressive speech. Moreover, privacy is ensured by running the decoding on-site and not on a remote server. Furthermore the system was biased to recognize only set of sentences. The system has been evaluated in a smart space reproducing a typical living room where 17 participants played scenarios including falls. The results showed a promising error rate, 29%, while emphasizing the challenges of the task.Cet article présente un système capable de reconnaître les appels à l'aide de personnes âgées vivant à domicile afin de leur fournir une assistance. Le système utilise une technologie de Reconnaissance Automatique de la Parole (RAP) qui doit fonctionner en conditions de parole distante et avec de la parole expressive. Pour garantir l'intimité, le système s'exécute localement et ne reconnaît que des phrases prédéfinies. Le système a été évalué par 17 participants jouant des scénarios incluant des chutes dans un Living lab reproduisant un salon. Le taux d'erreur de détection obtenu, 29%, est encourageant et souligne les défis à surmonter pour cette tâche

Recognition of Distress Calls in Distant Speech Setting: a Preliminary Experiment in a Smart Home

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