Objective
The key research questions explored were:
-How can auditory processing performed in the cochlea be simulated?
-How can the transient information concerning the onsets and offsets of parts of speech be extracted from an early stage of the auditory processing chain?
-How can existing connectionist recognisers be developed to perform vowel recognition using the cochlea simulation as a front-end ?
-How can training techniques for connectionist recognisers be improved?
-How do humans perform on a phoneme recognition task in the absence of lexical and contextual constraints?
The computer modelling of auditory processing and connectionist systems for speech recognition was addressed. Based on research into peripheral auditory processing and cognitive research on speech perception and memory, the primary goal was to develop a recognition system that benefits from the processing embodied in current models of the human auditory system.
At the present time, developed software and published research on the project include:
an efficient computer simulation of cochlea processing, documentation of the software for users in speech recognition and hearing research and published papers describing experiments on octave perception and phoneme recognition;
efficient implementation of a connectionist recognizer producing performance comparable to the best fast Fourier transform (FET) filterbank and improved training and pattern recognition algorithms;
experimental research on the structure of human phonological memory.
APPROACH AND METHODS
The goal was to construct a recognition system involving a high-resolution front-end processor based on current models of the human auditory system, and a word-recognition system based on abstract phonological representations and a phonological buffer store.
The three parallel research streams aimed to:
-Develop a detailed but efficient functional model of human hearing in five stages: spectral analysis, neural transduction, phase allignment, pitch extraction and timbre stabilisation. Feature extraction mechanisms used in the model were to be developedin line with psychological research.
-Compare connectionist recogniser performance using auditory preprocessing with conventional spectrographic preprocessing.
-Develop new recogniser architectures and training algorithms in line with psycholinguistic research.
Work was also directed towards developing user documentation for the cochlea simulation software, establishing base-line performance for phoneme recognition using both traditional and auditory front-ends, feature extraction software, and an efficient parallel implementation of a connectionist recogniser. Phonological memory research, experimentation concerning human vowel recognition and human psycho-acoustical research are continuing parts of the Action.
PROGRESS AND RESULTS
At the present time, developed software and published research on the Action include:
-An efficient computer simulation of cochlea processing; documentation of the software for users in speech recognition and hearing research; published papers describing experiments on octave perception and phoneme recognition.
-Efficient implementation of a connectionist recogniser producing performance comparable to the best HMM recognisers; comparisons of the auditory model front-end with an FFT filterbank; improved training and pattern-recognition algorithms.
-Experimental research on the structure of human phonological memory.
POTENTIAL
This Action is laying the foundations for the construction of balanced and efficient auditory connectionist speech recognition systems that are founded on cognitive research in the areas of speech perception and memory.
Fields of science (EuroSciVoc)
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
- natural sciences biological sciences neurobiology cognitive neuroscience
- natural sciences computer and information sciences artificial intelligence pattern recognition
- natural sciences computer and information sciences software software applications simulation software
- natural sciences mathematics applied mathematics mathematical model
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Coordinator
CB2 2EF Cambridge
United Kingdom
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