Professor Lahiri has held two ERC Advanced Grants in addition to two ERC Proof of Concept grants for work in this area, to carry out the fundamental investigation of variations in speech, leading to a linguistic model of speech based on phonological features, the articulatory and acoustic properties of each sound that form its contrasts with others. For example, the ‘voicing’ feature (whether the vocal cords are vibrating or not) forms a component of the contrast between the ‘p’ and ‘b’ consonant sounds in English.
The team developed the speech recognition system that was trained to recognise a universal set of 19 such features and can combine them to identify speech sounds, or phones. Importantly, it targets those features, essential to human understanding of speech, and ignores or tolerates those that can vary across speakers or utterances.
The research team has also used this model to develop a language learning app. which analyses words and sentences spoken by the user, and provides detailed feedback, so language learners can receive personalised responses to improve their pronunciation.
The novel inventions for Automatic Speech Recognition and a System for Automatic Speech Analysis
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