phoneme recognition research paper-11

phoneme recognition research paper-11





Towards lower error rates in phoneme recognition
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We investigate techniques for acoustic modeling in automatic recognition of context- independent phoneme strings from the TIMIT database. The baseline phoneme recognizer is based on TempoRAl Patterns (TRAP). This recognizer is simplified to shorten

Bidirectional LSTM networks for improved phoneme classification and recognition
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In this paper, we carry out two experiments on the TIMIT speech corpus with bidirectional and unidirectional Long Short Term Memory (LSTM) networks. In the first experiment (framewise phoneme classification) we find that bidirectional LSTM outperforms both

A support vector/hidden Markov model approach to phoneme recognition
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ABSTRACT A novel method for classifying frames of speech waveforms to a given set of phoneme classes is proposed. The method involves combining an approximation to multiple smoothing spline logistic regression (known as the Support Vector Machine in the

Support vector machines for Thai phoneme recognition
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The Support Vector Machine (SVM) has recently been introduced as a new pattern classification technique. It learns the boundary regions between samples belonging to two classes by mapping the input samples into a high dimensional space, and seeking a

Phoneme recognition in popular music
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ABSTRACT Automatic lyrics synchronization for karaoke applications is a major challenge in the field of music information retrieval. An important pre-requisite in order to precisely synchronize the music and corresponding text is the detection of single phonemes in the

Experiments with artificial neural networks for phoneme and word recognition
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ABSTRACT An artificial neural network has been trained by the error back-propagation technique to recognise phonemes and words. The speech material was recorded by a male Swedish talker and was labelled by a phonetician. There were 38 output nodes

Automatic syllable-based phoneme recognition using ESTER corpus
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ABSTRACT This paper presents an evaluation of speaker-independent continuous phoneme recognition systems on the French speech database ESTER. The tested systems are syllable-based phoneme recognizers, ie they use syllables as basic units together with

Phoneme recognition with large hierarchical reservoirs
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ABSTRACT Automatic speech recognition has gradually improved over the years, but the reliable recognition of unconstrained speech is still not within reach. In order to achieve a breakthrough, many research groups are now investigating new methodologies that have

The effect of rate stimulation of the auditory nerve on phoneme recognition
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ABSTRACT Five patients implanted with the Nucleus CI-24M cochlear implant were tested on consonant and vowel perception with three different average rates of stimulation: 250 pulses/s per channel, 807 pps/ch and 1615 pps/ch. There were no significant differences

A hierarchical approach to phoneme recognition of fluent speech
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ABSTRACT An overview is presented of a hierarchical phoneme recognition system which performs the task in a number of steps: segmentation, manner of articulation classification and then place of articulation classification. A combination of knowledge-based

Significance of contextual information in phoneme recognition
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2 IDIAP–RR 07-28 n this paper, we investigate the significance of contextual information at various stages in the development of a phoneme recognition system using an artificial neural network. A phoneme is treated as made up of three sub-phonemic states

Song wave retrieval based on frame-wise phoneme recognition We propose a song wave retrieval method. Both song wave data and a query wave for song wave data are transformed into phoneme sequences by frame-wise labeling of each frame feature. By applying a search algorithm, called Continuous Dynamic Programming (CDP),

TDNN vs. Fully Interconnected Multilayer Perceptron: A Comparative Study on Phoneme Recognition
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ABSTRACT The development and performance of a Time-Delay Neural Network (TDNN) and a Fully Interconnected Neural Network (FINN) is compared for continuous speech, speaker-independent recognition of voiced stops and unvoiced fricatives from the DARPA

Comparative phonetic analysis and phoneme recognition for Afrikaans, English and Xhosa using the African Speech Technology telephone speech databases
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ABSTRACT This paper concerns the Afrikaans, English and Xhosa speech databases recently developed as part of the African Speech Technology project. The three corpora are analysed and compared in terms of their phonetic content, diversity and mutual overlap.

Phoneme lattice based A* search algorithm for speech recognition
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This paper presents the Speeral continuous speech recognition system developed in the LIA. Speeral uses a modified A* algorithm to find in the search graph the best path taking into account acoustic and linguistic constraints. Rather than words by words, the A* used

Least Squares Support Vector Machine based Phoneme Recognition
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ABSTRACT Support Vector Machines (SVMs) have become a popular classification tool. Because of their theoretical robustness they offer improvements in pattern classification applications. This paper describes an approach of producing a N-best list of hypotheses

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