Robust and Adaptive Information Processing for Mobile Speech Interfaces
نویسندگان
چکیده
While there are opportunities to using mobile devices, the challenges of exploiting mobile applications to the full involve the combination of several different technologies. Canon Research Centre Europe (CRE) is performing research and development in technologies that address these challenges, most notably: robust embedded speech recognition, multimodal interaction, and mobile information access. This talk gives an overview of the work being done at CRE with a special emphasis on how these themes are targeted at applications using mobile devices.
منابع مشابه
DUMAS – Adaptation and Robust Information Processing for Mobile Speech Interfaces
In this paper we present the EU-IST project DUMAS (Dynamic Universal Mobility for Adaptive Speech Interfaces), and discuss adaptation and robust information processing as realized in AthosMail, a speechbased multilingual email application developed within the project. AthosMail allows users to read and manipulate their mailbox via a mobile phone. One of the goals of the research conducted in th...
متن کاملNew Concept Service for the Mobile Era Using Speech Technologies
In this paper, we describe new concept services based on speech processing technologies for the new digital/mobile era called a ubiquitous society. First, we propose a compact and noise robust embedded speech recognition middleware implemented on microprocessors aiming for sophisticated HMIs (Human Machine Interfaces) of car information systems. The compactness is essential for embedded systems...
متن کاملAn Information-Theoretic Discussion of Convolutional Bottleneck Features for Robust Speech Recognition
Convolutional Neural Networks (CNNs) have been shown their performance in speech recognition systems for extracting features, and also acoustic modeling. In addition, CNNs have been used for robust speech recognition and competitive results have been reported. Convolutive Bottleneck Network (CBN) is a kind of CNNs which has a bottleneck layer among its fully connected layers. The bottleneck fea...
متن کاملRobust Semantic Analysis for Adaptive Speech Interfaces
The DUMAS project develops speech-based applications that are adaptable to different users and domains. The paper describes the project’s robust semantic analysis strategy, used both in the generic framework for the development of multilingual speech-based dialogue systems which is the main project goal, and in the initial test application, a mobile phone-based e-mail interface.
متن کاملImproving the performance of MFCC for Persian robust speech recognition
The Mel Frequency cepstral coefficients are the most widely used feature in speech recognition but they are very sensitive to noise. In this paper to achieve a satisfactorily performance in Automatic Speech Recognition (ASR) applications we introduce a noise robust new set of MFCC vector estimated through following steps. First, spectral mean normalization is a pre-processing which applies to t...
متن کامل