phoneme recognition research paper-1001


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Tandem MLNs based Phonetic Feature Extraction for Phoneme Recognition
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Abstract: This paper presents a method for automatic phoneme recognition for Japanese
language using tandem MLNs. Here, an accurate phoneme recognizer or phonetic type-
writer, which extracts out-of-vocabulary (OOV) word for resolving OOV problem that 

SPEAKER INDEPENDENT PHONEME RECOGNITION USING NEURAL NETWORKS
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NU Maheswari, AP Kabilan ,2005 ,uceresource.org
ABSTRACT Phoneme recognition is important for successful development of speech
recognizers in most real world applications. While speaker dependent phoneme recognizers
have achieved close to 100% accuracy, the speaker independent phoneme recognition 

PHONEME RECOGNITION USING MULTI-LAYER PERCEPTRONS
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K Elenius ,speech.kth.se
ABSTRACT An artificial neural network has been trained to recognizes phonemes using the
error back-propagation technique. First a coarse feature network was trained to extract
seven quasi-phonetic features from the spectral frames of a Bark-scaled filter bank. The 

Audio–Visual Feature Extreaction for Phoneme Recognition of Meetings
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This document is dealing with an audio-visual feature extraction system used in a task of
phoneme recognition of meeting recordings. Generally used data is meeting recordings
developed at IDIAP [5],[14]. The goal of this work is to employ visual features extracted 

New variant of the Self Organizing Map in Pulsed Neural Networks to Improve Phoneme Recognition in Continuous Speech
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T Behi, N Arous ,International Journal of , 2012 ,research.ijcaonline.org
ABSTRACT Speech recognition has gradually improved over the years, phoneme
recognition in particular. Phoneme recognition plays very important role in speech
processing. Phoneme strings are basic representation for automatic language recognition 

The Second Joint Meeting of ASA and ASJ, Nov. 1988 PPP23. The relationships betweenphoneme recognition accuracy and sentence recognition accuracy
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Y Ohguro ,slp.ics.tut.ac.jp
ABSTRACT The relationships between phoneme recognition accuracy and sentence
recognition accuracy for continuous speech recognition using a simulated phoneme
recognizer are described. A left-to-right and topdown parser based on Earley’s algorithm 

Broadcast News Phoneme Recognition by Sparse Coding
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J Razik, S Paris ,razik.univ-tln.fr
Abstract: We present in this paper a novel approach for the phoneme recognition task that
we want to extend to an automatic speech recognition system (ASR). Usual ASR systems
are based on a GMM-HMM combination that represents a fully generative approach. 

Continuous Speech Phoneme Recognition Using Dynamic Artificial Neural Networks
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D József ,ms.sapientia.ro
Abstract: Phoneme classification and recognition is the first step to large vocabulary
continuous speech recognition. This step represents the acoustic modeling part of such a
system. In hybrid speech recognition systems phoneme recognition is made by artificial 

Phoneme-based Recognition of Finnish Words with Dynamic Dictionaries
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 T Seppänen, J Peltola ,msas.maliwatch.org
Abstract: In this paper we present an isolated-word recognition system using first HMM to
recognize the underlying sequence of phonemes, then DP and phoneme n-gram matching
techniques to determi ne the corresponding nearest idealized phoneme sequences in the 

A SPEAKER INDEPENDENT PHONEME RECOGNITION SYSTEM
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A Tridgeli ,assta.org
ABSTRACT-A speaker independent phoneme recognition system is presented and
discussed. Some of the unique features of this system include the use of a tree based vector
quantiser and the use of multiple vector quantisers for each parameter set.

SPOKEN INTERFACE FOR CORRECTING PHONEME RECOGNITION ERRORS IN LEARNING OF UNKNOWN WORDS
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X Zuo, T Sumii, N Iwahashi, M Nakano ,kaigi.org
This paper describes a novel method that enables users to teach systems the phoneme
sequences of new words through speech interaction. Using the method, users can correct
mis-recognized phoneme sequences incrementally by making corrective utterances. Each 

 recognition rate, perplexity and sentence recognition rate”‘Many measurements have been proposed and used to measure the complexity of speech recognition 
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S Nakagawa ,slp.ics.tut.ac.jp
The matching score between an input word and the corresponding reference pattern is
regarded as a sample from a normal distribution N (ß lt o* x2). On the other hand, the score
between the input word and the wrong reference pattern is regarded as a sample from the 

DEEP-HIDDEN CONDITIONAL NEURAL FIELDS FOR CONTINUOUS PHONEME SPEECHRECOGNITION
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Y Fujii, K Yamamoto ,ism.ac.jp
ABSTRACT We have proposed Hidden Conditional Neural Fields (HCNF) for automatic
speech recognition and shown the effectiveness by continuous phoneme recognition
experiments on the TIMIT and the Japanese ASJ+ JNAS corpora. In this paper, we 

Phoneme recognition for the hearing impaired
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M Blomberg ,2002 ,speech.kth.se
Abstract This paper describes an automatic speech recognition system designed to
investigate the use of phoneme recognition as a hearing aid in telephone communication.
The system was tested in two experiments. The first involved 19 normal hearing subjects 

Critical Review: Based on its effect on speech and phoneme recognition in children, should frequency lowering be used in pediatric amplification?
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I Nicholaou ,2012 ,uwo.ca
Abstract: The purpose of this critical review is to evaluate the effect of frequency lowering
(FL) technology on speech recognition in the pediatric population. One of each of the
following study designs were included: a within groups, repeated measure design; a 

Analysis of Recurrent Neural Networks with Application to Speaker Independent Phoneme Recognition
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ILPJ Veelenturf ,1999 ,eskodijk.nl
Summary This report investigates how recurrent neural networks can be applied to the task
of speaker independent phoneme recognition. Several recurrent neural network
architectures found in literature are listed and categorized. A general modular description 

Adaptive Feature Extraction with Spike Coding for ANN Based Phoneme Recognition
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Abstract Most speech recognition systems rely on spectral based features or others derived
from them (eg Mel frequency cepstral coefficients). These features are usually adjusted
according to the psychoacoustic properties of the human or human-like auditory systems 

Kernel Logistic Regression for Phoneme Recognition
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  ulb.ac.be
This research studies the extension of a multiclass logistic regression technique for the task
of phoneme recognition. Herefor, a kernel version is derived based on a penalized
likelihood criterion. The choice of this approach over an empirical risk minimization 

Recognition of Hindi Phoneme in Rhyming Words using Vector Quantization
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S Sinha, SGM Gaur ,desceco.org
Abstract This paper presents and discusses the recognition of Phoneme in Rhyming word
environment using Vector Quantization. Recognition has been carried out on rhyming words
extracted from Hindi speech database. Our objective of study is to evaluate and compare 

Phoneme recognition as a function of the number of auditory filter outputs
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F Apoux ,Journal of the Acoustical Society of America, 2008 ,webistem.com
It has been proposed that listeners take advantage of brief coups d’oeil when processing
speech in noise. These glimpses can be characterized both in time and frequency. The
obligatory role of the auditory filters in determining the nature of any further processing 

PHONEME RECOGNITION BASED ON LONG TEMPORAL CONTEXT
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PR ACE, P SCHWARZ ,fit.vutbr.cz
Abstract Techniques for automatic phoneme recognition from spoken speech are
investigated. The goal is to extract as much information about phoneme from as long
temporal context as possible. The Hidden Markov Model/Artificial Neural Network (HMM/ 

ONLINE DISCRIMINATIVE LEARNING OF PHONEME RECOGNITION VIA COLLECTIONS OF GENERALIZED LINEAR MODELS
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K Crammer ,webee.technion.ac.il
ABSTRACT We describe a new online discriminative learning algorithm that efficiently and
effectively recognizes phonemes in a speech sequence. The method builds upon recent
work in online learning of a collection of generalized linear models using second order 

Modeling Phoneme and Open-Set Word Recognition by Cochlear Implant Users Based on Psychophysical Performance: A Preliminary Report1
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Abstract. We have recently made some progress in our ability to explain perceptual
performance by adult cochlear implant (CI) users, and this research may eventually be
applicable to children. Quantitative, psychophysically-based models of vowel (Svirsky & 

Audio-Visual Speech Recognition Based on AAM Parameter and Phoneme Analysis of Visual Feature
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Y Komai, Y Ariki ,Advances in Image and Video Technology, 2012 ,Springer
As one of the techniques for robust speech recognition under noisy environment, audio-
visual speech recognition using lip dynamic visual information together with audio
information is attracting attention and the research is advanced in recent years. Since 


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