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A Proposal for a Kernel-based Algorithm for Large Vocabulary Continuous Speech Recognition

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The Movement Error Rate for Evaluation of Machine Learning Methods for sEMG-based Hand Movement Classification

Barbara Caputo

There has been increasing interest in applying learning algorithms to improve the dexterity of myoelectric prostheses. In this work, we present a large-scale benchmark evaluation on the second iteration of the publicly released NinaPro database, which cont ...

2014

Syllable-based Pitch Encoding for Low Bit Rate Speech Coding with Recognition/Synthesis Architecture

Philip Neil Garner, Milos Cernak

Current HMM-based low bit rate speech coding systems work with phonetic vocoders. Pitch contour coding (on frame or phoneme level) is usually fairly orthogonal to other speech coding parameters. We make an assumption in our work that the speech signal cont ...

Idiap2013

A Kernel Wrapper for Phoneme Sequence Recognition

We describe a kernel wrapper, a Mercer kernel for the task of phoneme sequence recognition which is based on operations with the Gaussian kernel, and suitable for any sequence kernel classifier. We start by presenting a kernel-based algorithm for phoneme s ...

John Wiley and Sons2009

An Ad Hoc Information Retrieval Perspective on PLSI through language model identification

Jean-Cédric Chappelier, Emmanuel Eckard

Ten years ago, PLSI opened the road to probabilistic latent semantic representations of documents. It led to a number of applications in different ﬁelds, including ad hoc Information Retrieval. However, inherent limitations hinder its use on documents not ...

Springer-Verlag New York, Ms Ingrid Cunningham, 175 Fifth Ave, New York, Ny 10010 Usa2009

Composite Kernel Learning

The Support Vector Machine (SVM) is an acknowledged powerful tool for building classifiers, but it lacks flexibility, in the sense that the kernel is chosen prior to learning. Multiple Kernel Learning (MKL) enables to learn the kernel, from an ensemble of ...

Omnipress2008

Composite Kernel Learning

IDIAP2008

Emulating Temporal Receptive Fields of Higher Level Auditory Neurons for ASR

Hynek Hermansky

This paper proposes modifications to the Multi-resolution RASTA (MRASTA) feature extraction technique for the automatic speech recognition (ASR). By emulating asymmetries of the temporal receptive field (TRF) profiles of higher level auditory neurons, we o ...

Springer-Verlag New York, Ms Ingrid Cunningham, 175 Fifth Ave, New York, Ny 10010 Usa2008

Fast Approximate Spoken Term Detection from Sequence of Phonemes

Hynek Hermansky, Joel Praveen Pinto

We investigate the detection of spoken terms in conversational speech using phoneme recognition with the objective of achieving smaller index size as well as faster search speed. Speech is processed and indexed as a sequence of one best phoneme sequence. W ...

2008

Fast Approximate Spoken Term Detection from Sequence of Phonemes

Hynek Hermansky, Joel Praveen Pinto

IDIAP2008

Hilbert Envelope Based Features for Far-Field Speech Recognition

Hynek Hermansky, Sriram Ganapathy, Samuel Thomas

Automatic speech recognition (ASR) systems, trained on speech signals from close-talking microphones, generally fail in recognizing far-field speech. In this paper, we present a Hilbert Envelope based feature extraction technique to alleviate the artifacts ...

2008