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- W2807727752 abstract "This paper presents a comparison of three spectral features for automatic phone recognition in sub-optimal environments. An exclusive study is carried out with a phone recognition system called phonetic engine (PE) developed in the Manipuri language. The Manipuri language is a scheduled Indian language being used as the official language in the State of Manipur. However, there is no standard database of the language so far. Therefore, a PE has been built for this language. Here phonetic transcriptions are done and then modeling of each phonetic unit is carried out using hidden Markov model (HMM). Speech feature extraction is a very important stage in the development of such a PE. An analysis of phone recognition accuracies of the PE due the three dominant spectral features: MFCC, PLP and LPCC have been studied here. It is found that PLP and MFCC outperform LPCC features under all circumstances." @default.
- W2807727752 created "2018-06-21" @default.
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- W2807727752 date "2018-01-01" @default.
- W2807727752 modified "2023-09-27" @default.
- W2807727752 title "A comparison of three spectral features for phone recognition in sub-optimal environments" @default.
- W2807727752 doi "https://doi.org/10.1504/ijapr.2018.10013769" @default.
- W2807727752 hasPublicationYear "2018" @default.
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