Publications associées à Téléphonie large-bande

Subthreshold VO2 vertical switches for large-bandwidth millimeter-wave and sub-terahertz detection

Mihai Adrian Ionescu, Ali Gilani, Daesung Park, Fatemeh Qaderi Rahaqi

n-linear impedance characteristics of VO2 offer solutions to highly sensitive radio-frequency (RF), millimeterwave (mm-wave), and terahertz (THz) detectors. We demonstrate high-speed broadband sensibility of miniaturized VO2 switches by utilizing the nonli ...

IEEE2022

Predicting the intrusiveness of noise through sparse coding with auditory kernels

Hervé Bourlard, Raphaël Marc Ullmann

This paper presents a novel approach to predicting the intrusiveness of background noises in speech signals as it is perceived by human listeners. This problem is of particular interest in telephony, where the recently widened range of transmitted audio fr ...

2016

Sparse Gammatone Signal Model Predicts Perceived Noise Intrusiveness

Hervé Bourlard, Raphaël Marc Ullmann

Is it possible to predict the intrusiveness of background noise in speech signals as perceived by humans? Such a question is important to the automatic evaluation of speech enhancement systems, including those designed for new wideband speech telephony, an ...

Idiap2014

Implementation of an image recognition algorithm on the DM6446 DaVinci Processor

Pierre-André Farine, Sara Grassi Pauletti, Pradyumna Ayyalasomayajula

We are developing an Alternative and Augmentative Communication (AAC) portable device called PictoBar which is used in speech rehabilitation therapy. PictoBar recognizes barcodes and images, such as pictograms and pictures. Then it plays a sound message as ...

2010

Wide-Band Audio Coding based on Frequency Domain Linear Prediction

Petr Motlicek, Hynek Hermansky, Sriram Ganapathy

We revisit an original concept of speech coding in which the signal is separated into the carrier modulated by the signal envelope. A recently developed technique, called frequency-domain linear prediction (FDLP), is applied for the efficient estimation of ...

2010

Wide-Band Audio Coding based on Frequency Domain Linear Prediction

Petr Motlicek, Hynek Hermansky, Sriram Ganapathy

In this paper, we re-visit an original concept of speech coding in which the signal is separated into the carrier modulated by the signal envelope. A recently developed technique, called frequency domain linear prediction (FDLP), is applied for the efficie ...

Idiap2009

APPLICATIONS OF SIGNAL ANALYSIS USING AUTOREGRESSIVE MODELS FOR AMPLITUDE MODULATION

Petr Motlicek, Hynek Hermansky, Sriram Ganapathy, Samuel Thomas

Frequency Domain Linear Prediction (FDLP) represents an efficient technique for representing the long-term amplitude modulations (AM) of speech/audio signals using autoregressive models. For the proposed analysis technique, relatively long temporal segment ...

Idiap2009

APPLICATIONS OF SIGNAL ANALYSIS USING AUTOREGRESSIVE MODELS FOR AMPLITUDE MODULATION

Petr Motlicek, Hynek Hermansky, Sriram Ganapathy, Samuel Thomas

2009

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Téléphonie large-bande

Subthreshold VO2 vertical switches for large-bandwidth millimeter-wave and sub-terahertz detection

Multilingual and Unsupervised Subword Modeling for Zero-Resource Languages

Comparison of Compression Efficiency between HEVC/H.265, VP9 and AV1 based on Subjective Quality Assessments

Predicting the intrusiveness of noise through sparse coding with auditory kernels

Sparse Gammatone Signal Model Predicts Perceived Noise Intrusiveness

Implementation of an image recognition algorithm on the DM6446 DaVinci Processor

Wide-Band Audio Coding based on Frequency Domain Linear Prediction

Wide-Band Audio Coding based on Frequency Domain Linear Prediction

APPLICATIONS OF SIGNAL ANALYSIS USING AUTOREGRESSIVE MODELS FOR AMPLITUDE MODULATION

APPLICATIONS OF SIGNAL ANALYSIS USING AUTOREGRESSIVE MODELS FOR AMPLITUDE MODULATION

Graph Chatbot

Chattez avec Graph Search

Sparse Gammatone Signal Model Predicts Perceived Noise Intrusiveness

APPLICATIONS OF SIGNAL ANALYSIS USING AUTOREGRESSIVE MODELS FOR AMPLITUDE MODULATION

APPLICATIONS OF SIGNAL ANALYSIS USING AUTOREGRESSIVE MODELS FOR AMPLITUDE MODULATION

Comparison of Compression Efficiency between HEVC/H.265, VP9 and AV1 based on Subjective Quality Assessments

Wide-Band Audio Coding based on Frequency Domain Linear Prediction

Subthreshold VO2 vertical switches for large-bandwidth millimeter-wave and sub-terahertz detection

Multilingual and Unsupervised Subword Modeling for Zero-Resource Languages

Predicting the intrusiveness of noise through sparse coding with auditory kernels

Wide-Band Audio Coding based on Frequency Domain Linear Prediction

Implementation of an image recognition algorithm on the DM6446 DaVinci Processor