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MorSR SIGNED

Integrating morpho-phonology in speech recognition

Total Cost €

0

EC-Contrib. €

0

Partnership

0

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 MorSR project word cloud

Explore the words cloud of the MorSR project. It provides you a very rough idea of what is the project "MorSR" about.

fast    sufficient    substantial    machine    words    morphon    standard    word    running    natural    prohibitively    unlike    innovative    regularities    languages    grammatical    outcome    interface    spectrum    phonological    automatic    sequencing    written    prediction    reduces    man    considerably    linguistic    accurate    demonstrated    representation    rely    dramatically    enhanced    reduce    space    contrasts    central    principles    adapting    possibilities    commercial    expensive    obtaining    previously    instead    fine    translate    social    requiring    ing    model    reject    remove    erc    easily    isolated    grained    delivers    incorporate    barriers    speech    universal    probability    lost    training    recognition    subtle    data    adaptable    sequences    technological    corpora    acoustic    requirement    dialect    variation    language    capture    correct    structure    lm    improbable    secure    variants    morsr    strengths    probabilistic    signal    predictions    asr    phoneme    flexsr    search    deployment    accuracy    combined   

Project "MorSR" data sheet

The following table provides information about the project.

Coordinator
THE CHANCELLOR, MASTERS AND SCHOLARS OF THE UNIVERSITY OF OXFORD 

Organization address
address: WELLINGTON SQUARE UNIVERSITY OFFICES
city: OXFORD
postcode: OX1 2JD
website: www.ox.ac.uk

contact info
title: n.a.
name: n.a.
surname: n.a.
function: n.a.
email: n.a.
telephone: n.a.
fax: n.a.

 Coordinator Country United Kingdom [UK]
 Total cost 149˙919 €
 EC max contribution 149˙919 € (100%)
 Programme 1. H2020-EU.1.1. (EXCELLENT SCIENCE - European Research Council (ERC))
 Code Call ERC-2018-PoC
 Funding Scheme ERC-POC
 Starting year 2019
 Duration (year-month-day) from 2019-03-01   to  2020-08-31

 Partnership

Take a look of project's partnership.

# participants  country  role  EC contrib. [€] 
1    THE CHANCELLOR, MASTERS AND SCHOLARS OF THE UNIVERSITY OF OXFORD UK (OXFORD) coordinator 149˙919.00

Map

 Project objective

Automatic Speech Recognition (ASR) is considered to represent the most natural man-machine interface across the spectrum of technological space. Current commercial ASR systems rely on a ‘rich’ representation of an acoustic signal for words and their variants, resulting in major challenges in the deployment of ASR systems in areas where it could have substantial social impact. Our central goal is to translate research results from the ERC funded project MORPHON into a novel ASR system to remove such barriers. We have previously demonstrated that the use of a universal set of phonological features delivers an isolated word recognition system (FlexSR) with enhanced phoneme recognition accuracy. It is more robust under conditions of non-standard speech, dialect variation and can be easily adapted to new languages. These aspects are problematic for current ASR systems which rely on the probabilistic sequencing of whole words in their language model (LM) based on large written text corpora for training. Obtaining sufficient training data for a new LM is prohibitively expensive. Instead, MorSR will incorporate linguistic information about word-structure to reject improbable words. This reduces the search space and increases the probability of identifying correct words. A major outcome will be an innovative LM based on linguistic principles. Unlike existing approaches, it is based on speech data to capture crucial regularities that are lost in text corpora. Combined with FlexSR's key strengths in identifying subtle phonological contrasts, MorSR will not only enable improved predictions of word sequences in running speech, but also dramatically reduce the requirement for training data when adapting the system to a new language. MorSR's strengths include: (a) prediction of fine-grained possibilities of word sequences based on grammatical principles; (b) requiring considerably less training data; (c) easily adaptable to new languages; and (d) will be fast, secure and accurate.

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