Publication

Joint Decoding for Phoneme-Grapheme Continuous Speech Recognition

Hervé Bourlard, Mathew Magimai Doss
2004
Conference Papers

Abstract

Standard ASR systems typically use phoneme as the subword units. Preliminary studies have shown that the performance of the ASR system could be improved by using grapheme as additional subword units. In this paper, we investigate such a system where the word models are defined in terms of two different subword units, i.e., phoneme and grapheme. During training, models for both the subword units are trained, and then during recognition either both or just one subword unit is used. We have studied this system for a continuous speech recognition task in American English language. Our studies show that grapheme information used along with phoneme information improves the performance of ASR.

Official source

https://infoscience.epfl.ch/entities/publication/eed86eef-9afb-4379-82c1-efa07acdf959

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Hervé Bourlard, Mathew Magimai Doss
2004
Conference Papers

Abstract

Official source

https://infoscience.epfl.ch/entities/publication/eed86eef-9afb-4379-82c1-efa07acdf959

About this result

Related concepts (31)

Phonemic orthography

A phonemic orthography is an orthography (system for writing a language) in which the graphemes (written symbols) correspond to the phonemes (significant spoken sounds) of the language. Natural languages rarely have perfectly phonemic orthographies; a high degree of grapheme–phoneme correspondence can be expected in orthographies based on alphabetic writing systems, but they differ in how complete this correspondence is.

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.

Pattern recognition

Pattern recognition is the automated recognition of patterns and regularities in data. While similar, pattern recognition (PR) is not to be confused with pattern machines (PM) which may possess (PR) capabilities but their primary function is to distinguish and create emergent pattern. PR has applications in statistical data analysis, signal processing, , information retrieval, bioinformatics, data compression, computer graphics and machine learning.

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