LUCIA: An open source 3D expressive avatar for multimodal h.m.i.

LUCIA is an MPEG-4 facial animation system developed at ISTC-CNR . It works on standard Facial Animation Parameters and speaks with the Italian version of FESTIVAL TTS. To achieve an emotive/expressive talking head LUCIA was build from real human data physically extracted by ELITE optotracking movement analyzer. LUCIA can copy a real human by reproducing the movements of passive markers positioned on his face and recorded by the ELITE device or can be driven by an emotional XML tagged input text, thus realizing a true audio/visual emotive/expressive synthesis. Synchronization between visual and audio data is very important in order to create the correct WAV and FAP files needed for the animation. LUCIA\u27s voice is based on the ISTC Italian version of FESTIVAL-MBROLA packages, modified by means of an appropriate APML/VSML tagged language. LUCIA is available in two dif-ferent versions: an open source framework and the "work in progress" WebGL

Multimodal acquisition of articulatory data: Geometrical and temporal registration

International audienceAcquisition of dynamic articulatory data is of major importance for studying speech production. It turns out that one technique alone often is not enough to get a correct coverage of the whole vocal tract at a sufficient sampling rate. Ultrasound (US) imaging has been proposed as a good acquisition technique for the tongue surface because it offers a good temporal sampling, does not alter speech production, is cheap and widely available. However, it cannot be used alone and this paper describes a multimodal acquisition system which uses electromagnetography sensors to locate the US probe. The paper particularly focuses on the calibration of the ultrasound modality which is the key point of the system. This approach enables ultrasound data to be merged with other data. The use of the system is illustrated via an experiment consisting of measuring the minimal tongue to palate distance in order to evaluate and design Magnetic Resonance Imaging protocols well suited for the acquisition of 3D images of the vocal tract. Compared to manual registration of acquisition modalities which is often used in acquisition of articulatory data, the approach presented relies on automatic techniques well founded from geometrical and mathematical points of view

Interfaces de fala silenciosa multimodais para português europeu com base na articulação

Doutoramento conjunto MAPi em InformáticaThe concept of silent speech, when applied to Human-Computer Interaction (HCI), describes a system which allows for speech communication in the absence of an acoustic signal. By analyzing data gathered during different parts of the human speech production process, Silent Speech Interfaces (SSI) allow users with speech impairments to communicate with a system. SSI can also be used in the presence of environmental noise, and in situations in which privacy, confidentiality, or non-disturbance are important. Nonetheless, despite recent advances, performance and usability of Silent Speech systems still have much room for improvement. A better performance of such systems would enable their application in relevant areas, such as Ambient Assisted Living. Therefore, it is necessary to extend our understanding of the capabilities and limitations of silent speech modalities and to enhance their joint exploration. Thus, in this thesis, we have established several goals: (1) SSI language expansion to support European Portuguese; (2) overcome identified limitations of current SSI techniques to detect EP nasality (3) develop a Multimodal HCI approach for SSI based on non-invasive modalities; and (4) explore more direct measures in the Multimodal SSI for EP acquired from more invasive/obtrusive modalities, to be used as ground truth in articulation processes, enhancing our comprehension of other modalities. In order to achieve these goals and to support our research in this area, we have created a multimodal SSI framework that fosters leveraging modalities and combining information, supporting research in multimodal SSI. The proposed framework goes beyond the data acquisition process itself, including methods for online and offline synchronization, multimodal data processing, feature extraction, feature selection, analysis, classification and prototyping. Examples of applicability are provided for each stage of the framework. These include articulatory studies for HCI, the development of a multimodal SSI based on less invasive modalities and the use of ground truth information coming from more invasive/obtrusive modalities to overcome the limitations of other modalities. In the work here presented, we also apply existing methods in the area of SSI to EP for the first time, noting that nasal sounds may cause an inferior performance in some modalities. In this context, we propose a non-invasive solution for the detection of nasality based on a single Surface Electromyography sensor, conceivable of being included in a multimodal SSI.O conceito de fala silenciosa, quando aplicado a interação humano-computador, permite a comunicação na ausência de um sinal acústico. Através da análise de dados, recolhidos no processo de produção de fala humana, uma interface de fala silenciosa (referida como SSI, do inglês Silent Speech Interface) permite a utilizadores com deficiências ao nível da fala comunicar com um sistema. As SSI podem também ser usadas na presença de ruído ambiente, e em situações em que privacidade, confidencialidade, ou não perturbar, é importante. Contudo, apesar da evolução verificada recentemente, o desempenho e usabilidade de sistemas de fala silenciosa tem ainda uma grande margem de progressão. O aumento de desempenho destes sistemas possibilitaria assim a sua aplicação a áreas como Ambientes Assistidos. É desta forma fundamental alargar o nosso conhecimento sobre as capacidades e limitações das modalidades utilizadas para fala silenciosa e fomentar a sua exploração conjunta. Assim, foram estabelecidos vários objetivos para esta tese: (1) Expansão das linguagens suportadas por SSI com o Português Europeu; (2) Superar as limitações de técnicas de SSI atuais na deteção de nasalidade; (3) Desenvolver uma abordagem SSI multimodal para interação humano-computador, com base em modalidades não invasivas; (4) Explorar o uso de medidas diretas e complementares, adquiridas através de modalidades mais invasivas/intrusivas em configurações multimodais, que fornecem informação exata da articulação e permitem aumentar a nosso entendimento de outras modalidades. Para atingir os objetivos supramencionados e suportar a investigação nesta área procedeu-se à criação de uma plataforma SSI multimodal que potencia os meios para a exploração conjunta de modalidades. A plataforma proposta vai muito para além da simples aquisição de dados, incluindo também métodos para sincronização de modalidades, processamento de dados multimodais, extração e seleção de características, análise, classificação e prototipagem. Exemplos de aplicação para cada fase da plataforma incluem: estudos articulatórios para interação humano-computador, desenvolvimento de uma SSI multimodal com base em modalidades não invasivas, e o uso de informação exata com origem em modalidades invasivas/intrusivas para superar limitações de outras modalidades. No trabalho apresentado aplica-se ainda, pela primeira vez, métodos retirados do estado da arte ao Português Europeu, verificando-se que sons nasais podem causar um desempenho inferior de um sistema de fala silenciosa. Neste contexto, é proposta uma solução para a deteção de vogais nasais baseada num único sensor de eletromiografia, passível de ser integrada numa interface de fala silenciosa multimodal

Multimodal corpora for silent speech interaction

A Silent Speech Interface (SSI) allows for speech communication to take place in the absence of an acoustic signal. This type of interface is an alternative to conventional Automatic Speech Recognition which is not adequate for users with some speech impairments or in the presence of environmental noise. The work presented here produces the conditions to explore and analyze complex combinations of input modalities applicable in SSI research. By exploring non-invasive and promising modalities, we have selected the following sensing technologies used in human-computer interaction: Video and Depth input, Ultrasonic Doppler sensing and Surface Electromyography. This paper describes a novel data collection methodology where these independent streams of information are synchronously acquired with the aim of supporting research and development of a multimodal SSI. The reported recordings were divided into two rounds: a first one where the acquired data was silently uttered and a second round where speakers pronounced the scripted prompts in an audible and normal tone. In the first round of recordings, a total of 53.94 minutes were captured where 30.25% was estimated to be silent speech. In the second round of recordings, a total of 30.45 minutes were obtained and 30.05% of the recordings were audible speech.info:eu-repo/semantics/publishedVersio

TaL: a synchronised multi-speaker corpus of ultrasound tongue imaging, audio, and lip videos

We present the Tongue and Lips corpus (TaL), a multi-speaker corpus of audio, ultrasound tongue imaging, and lip videos. TaL consists of two parts: TaL1 is a set of six recording sessions of one professional voice talent, a male native speaker of English; TaL80 is a set of recording sessions of 81 native speakers of English without voice talent experience. Overall, the corpus contains 24 hours of parallel ultrasound, video, and audio data, of which approximately 13.5 hours are speech. This paper describes the corpus and presents benchmark results for the tasks of speech recognition, speech synthesis (articulatory-to-acoustic mapping), and automatic synchronisation of ultrasound to audio. The TaL corpus is publicly available under the CC BY-NC 4.0 license.Comment: 8 pages, 4 figures, Accepted to SLT2021, IEEE Spoken Language Technology Worksho

A FACIAL ANIMATION FRAMEWORK WITH EMOTIVE/EXPRESSIVE CAPABILITIES

LUCIA is an MPEG-4 facial animation system developed at ISTC-CNR.. It works on standard Facial Animation Parameters and speaks with the Italian version of FESTIVAL TTS. To achieve an emotive/expressive talking head LUCIA was build from real human data physically extracted by ELITE optotracking movement analyzer. LUCIA can copy a real human by reproducing the movements of passive markers positioned on his face and recorded by the ELITE device or can be driven by an emotional XML tagged input text, thus realizing a true audio/visual emotive/expressive synthesis. Synchronization between visual and audio data is very important in order to create the correct WAV and FAP files needed for the animation. LUCIA\u27s voice is based on the ISTC Italian version of FESTIVAL-MBROLA packages, modified by means of an appropriate APML/VSML tagged language. LUCIA is available in two different versions: an open source framework and the "work in progress" WebG

Emerging Linguistic Functions in Early Infancy

This paper presents results from experimental studies on early language acquisition in infants and attempts to interpret the experimental results within the framework of the Ecological Theory of Language Acquisition (ETLA) recently proposed by (Lacerda et al., 2004a). From this perspective, the infant’s first steps in the acquisition of the ambient language are seen as a consequence of the infant’s general capacity to represent sensory input and the infant’s interaction with other actors in its immediate ecological environment. On the basis of available experimental evidence, it will be argued that ETLA offers a productive alternative to traditional descriptive views of the language acquisition process by presenting an operative model of how early linguistic function may emerge through interaction