Publication

Integrated Pronunciation Learning for Automatic Speech Recognition Using Probabilistic Lexical Modeling

Mathew Magimai Doss
2015
Conference Papers

Abstract

Standard automatic speech recognition (ASR) systems use phoneme-based pronunciation lexicon prepared by linguistic experts. When the hand crafted pronunciations fail to cover the vocabulary of a new domain, a grapheme-to-phoneme (G2P) converter is used to extract pronunciations for new words and then a phoneme- based ASR system is trained. G2P converters are typically trained only on the existing lexicons. In this paper, we propose a grapheme-based ASR approach in the framework of probabilistic lexical modeling that integrates pronunciation learning as a stage in ASR system training, and exploits both acoustic and lexical resources (not necessarily from the domain or language of interest). The proposed approach is evaluated on four lexical resource constrained ASR tasks and compared with the conventional two stage approach where G2P training is followed by ASR system development.

Official source

https://infoscience.epfl.ch/entities/publication/ee6184ab-1967-41fd-8e46-f966357ef971

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Mathew Magimai Doss
2015
Conference Papers

Abstract

Official source

https://infoscience.epfl.ch/entities/publication/ee6184ab-1967-41fd-8e46-f966357ef971

About this result

Related concepts (31)

Speech recognition

Speech recognition is an interdisciplinary subfield of computer science and computational linguistics that develops methodologies and technologies that enable the recognition and translation of spoken language into text by computers. It is also known as automatic speech recognition (ASR), computer speech recognition or speech to text (STT). It incorporates knowledge and research in the computer science, linguistics and computer engineering fields. The reverse process is speech synthesis.

Computer-assisted language learning

Computer-assisted language learning (CALL), British, or Computer-Aided Instruction (CAI)/Computer-Aided Language Instruction (CALI), American, is briefly defined in a seminal work by Levy (1997: p. 1) as "the search for and study of applications of the computer in language teaching and learning". CALL embraces a wide range of information and communications technology applications and approaches to teaching and learning foreign languages, from the "traditional" drill-and-practice programs that characterised CALL in the 1960s and 1970s to more recent manifestations of CALL, e.

Lexical Markup Framework

Language resource management Lexical markup framework (LMF; ISO 24613:2008), is the International Organization for Standardization ISO/TC37 standard for natural language processing (NLP) and machine-readable dictionary (MRD) lexicons. The scope is standardization of principles and methods relating to language resources in the contexts of multilingual communication. The goals of LMF are to provide a common model for the creation and use of lexical resources, to manage the exchange of data between and among these resources, and to enable the merging of large number of individual electronic resources to form extensive global electronic resources.

Related publications (4)

Integrated Pronunciation Learning for Automatic Speech Recognition Using Probabilistic Lexical Modeling

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