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Phoneme Recognition using Boosted Binary Features

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Learning multivariate new physics

Raffaele Tito D'Agnolo, Andrea Wulzer

We discuss a method that employs a multilayer perceptron to detect deviations from a reference model in large multivariate datasets. Our data analysis strategy does not rely on any prior assumption on the nature of the deviation. It is designed to be sensi ...

SPRINGER2021

Mixed-Precision Deep Learning Based on Computational Memory

Irem Boybat Kara, Evangelos Eleftheriou, Abu Sebastian

Deep neural networks (DNNs) have revolutionized the field of artificial intelligence and have achieved unprecedented success in cognitive tasks such as image and speech recognition. Training of large DNNs, however, is computationally intensive and this has ...

FRONTIERS MEDIA SA2020

Accelerating Gradient Boosting Machines

Sai Praneeth Reddy Karimireddy

Gradient Boosting Machine (GBM) introduced by Friedman (2001) is a widely popular ensembling technique and is routinely used in competitions such as Kaggle and the KDD-Cup (Chen and Guestrin, 2016). In this work, we propose an Accelerated Gradient Boosting ...

ADDISON-WESLEY PUBL CO2020

EMPIRICAL EVALUATION AND COMBINATION OF PUNCTUATION PREDICTION MODELS APPLIED TO BROADCAST NEWS

Philip Neil Garner

Natural language processing techniques are dependent upon punctuation to work well. When their input is taken from speech recognition, it is necessary to reconstruct the punctuation; in particular sentence boundaries. We define a range of features from low ...

2019

EMPIRICAL EVALUATION AND COMBINATION OF PUNCTUATION PREDICTION MODELS APPLIED TO BROADCAST NEWS

Philip Neil Garner

Idiap2019

On Learning to Identify Genders from Raw Speech Signal Using CNNs

Hannah Muckenhirn, Selen Hande Kabil

Automatic Gender Recognition (AGR) is the task of identifying the gender of a speaker given a speech signal. Standard approaches extract features like fundamental frequency and cepstral features from the speech signal and train a binary classifier. Inspire ...

ISCA-INT SPEECH COMMUNICATION ASSOC2018

Comparative Study on Sentence Boundary Prediction for German and English Broadcast News

Philip Neil Garner, David Imseng, Yang Wang

We present a comparative study on sentence boundary prediction for German and English broadcast news that explores generalization across different languages. In the feature extraction stage, word pause duration is firstly extracted from word aligned speech ...

Idiap2017

Towards End-to-End Speech Recognition

Dimitri Palaz

Standard automatic speech recognition (ASR) systems follow a divide and conquer approach to convert speech into text. Alternately, the end goal is achieved by a combination of sub-tasks, namely, feature extraction, acoustic modeling and sequence decoding, ...

EPFL2016

Adaptive Sampling for Large Scale Boosting

François Fleuret, Charles Dubout

Classical Boosting algorithms, such as AdaBoost, build a strong classifier without concern for the computational cost. Some applications, in particular in computer vision, may involve millions of training examples and very large feature spaces. In such con ...

2014

Object Classification and Detection in High Dimensional Feature Space

Charles Dubout

Object classification and detection aim at recognizing and localizing objects in real-world images. They are fundamental computer vision problems and a prerequisite for full scene understanding. Their difficulty lies in the large number of possible object ...

Programme doctoral en Informatique, Communications et Information2013