ABSTRACT This paper presents an overview of the Mobile Data Challenge (MDC), a large-scale resear... more ABSTRACT This paper presents an overview of the Mobile Data Challenge (MDC), a large-scale research initiative aimed at generating innovations around smartphone-based research, as well as community-based evaluation of mobile data analysis methodologies. First, we review the Lausanne Data Collection Campaign (LDCC), an initiative to collect unique longitudinal smartphone dataset for the MDC. Then, we introduce the Open and Dedicated Tracks of the MDC, describe the specific datasets used in each of them, discuss the key design and implementation aspects introduced in order to generate privacy-preserving and scientifically relevant mobile data resources for wider use by the research community, and summarize the main research trends found among the 100+ challenge submissions. We finalize by discussing the main lessons learned from the participation of several hundred researchers worldwide in the MDC Tracks.
Abstract-A number of applications of man-machine interaction over the telephone requires a combin... more Abstract-A number of applications of man-machine interaction over the telephone requires a combination of speech recognition and speaker verification. This paper de-scribes current work carried out at IDIAP in the frame-work of national and European projects. A generic In-ter. ...
Dalle Moue Institute for Perceptual Artificial Intelligence (IDIAP) CP 592, CH-1920 Martigny, Swi... more Dalle Moue Institute for Perceptual Artificial Intelligence (IDIAP) CP 592, CH-1920 Martigny, Switzerland ... In this paper, we attempt to validate the flexible vocabulary approach for speaker independent isolated word and con-nected words recognition. We compare the performance of ...
ABSTRACT this paper we describe an applied research project entitled "Automatic Speech R... more ABSTRACT this paper we describe an applied research project entitled "Automatic Speech Recognition in French on Workstation with SwissNet Connection". This cooperative project involves specialists from two research institutes: the Signal Processing Laboratory (LTS) of the Swiss Federal Institute of Technology Lausanne (EPFL) and the Dalle Molle Institute for Perceptive Artificial Intelligence, Martigny (IDIAP), and three industrial partners: aComm,SunMicrosystems (Switzerland) and the Swiss Telecom PTT. The project is supported by the Commission for Technology and Innovation (CTI, formerly CERS). The goal of the project is to make available basic technologies for automatic speech recognition (ASR) and speaker verification (SV) on multi-processor SunSPARCstation 20 and SwissNet platform to industrial partners and particularly to Swiss industry for Swiss French.
This paper presents an overview of the Mobile Data Challenge (MDC), a large-scale research initia... more This paper presents an overview of the Mobile Data Challenge (MDC), a large-scale research initiative aimed at generating innovations around smartphone-based research, as well as community-based evaluation of related mobile data analysis methodologies. First we review the Lausanne Data Collection Campaign (LDCC) -an initiative to collect unique, longitudinal smartphone data set for the basis of the MDC. Then, we introduce the Open and Dedicated Tracks of the MDC; describe the specific data sets used in each of them; and discuss some of the key aspects in order to generate privacy-respecting, challenging, and scientifically relevant mobile data resources for wider use of the research community. The concluding remarks will summarize the paper.
ABSTRACT This paper presents an overview of the Mobile Data Challenge (MDC), a large-scale resear... more ABSTRACT This paper presents an overview of the Mobile Data Challenge (MDC), a large-scale research initiative aimed at generating innovations around smartphone-based research, as well as community-based evaluation of mobile data analysis methodologies. First, we review the Lausanne Data Collection Campaign (LDCC), an initiative to collect unique longitudinal smartphone dataset for the MDC. Then, we introduce the Open and Dedicated Tracks of the MDC, describe the specific datasets used in each of them, discuss the key design and implementation aspects introduced in order to generate privacy-preserving and scientifically relevant mobile data resources for wider use by the research community, and summarize the main research trends found among the 100+ challenge submissions. We finalize by discussing the main lessons learned from the participation of several hundred researchers worldwide in the MDC Tracks.
Abstract-A number of applications of man-machine interaction over the telephone requires a combin... more Abstract-A number of applications of man-machine interaction over the telephone requires a combination of speech recognition and speaker verification. This paper de-scribes current work carried out at IDIAP in the frame-work of national and European projects. A generic In-ter. ...
Dalle Moue Institute for Perceptual Artificial Intelligence (IDIAP) CP 592, CH-1920 Martigny, Swi... more Dalle Moue Institute for Perceptual Artificial Intelligence (IDIAP) CP 592, CH-1920 Martigny, Switzerland ... In this paper, we attempt to validate the flexible vocabulary approach for speaker independent isolated word and con-nected words recognition. We compare the performance of ...
ABSTRACT this paper we describe an applied research project entitled "Automatic Speech R... more ABSTRACT this paper we describe an applied research project entitled "Automatic Speech Recognition in French on Workstation with SwissNet Connection". This cooperative project involves specialists from two research institutes: the Signal Processing Laboratory (LTS) of the Swiss Federal Institute of Technology Lausanne (EPFL) and the Dalle Molle Institute for Perceptive Artificial Intelligence, Martigny (IDIAP), and three industrial partners: aComm,SunMicrosystems (Switzerland) and the Swiss Telecom PTT. The project is supported by the Commission for Technology and Innovation (CTI, formerly CERS). The goal of the project is to make available basic technologies for automatic speech recognition (ASR) and speaker verification (SV) on multi-processor SunSPARCstation 20 and SwissNet platform to industrial partners and particularly to Swiss industry for Swiss French.
This paper presents an overview of the Mobile Data Challenge (MDC), a large-scale research initia... more This paper presents an overview of the Mobile Data Challenge (MDC), a large-scale research initiative aimed at generating innovations around smartphone-based research, as well as community-based evaluation of related mobile data analysis methodologies. First we review the Lausanne Data Collection Campaign (LDCC) -an initiative to collect unique, longitudinal smartphone data set for the basis of the MDC. Then, we introduce the Open and Dedicated Tracks of the MDC; describe the specific data sets used in each of them; and discuss some of the key aspects in order to generate privacy-respecting, challenging, and scientifically relevant mobile data resources for wider use of the research community. The concluding remarks will summarize the paper.
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Papers by O. Bornet