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Multilingual phone recognition in In...

K. E., Manjunath.

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Multilingual phone recognition in Indian languages

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Multilingual phone recognition in Indian languages/ by Manjunath K. E.
作者:	K. E., Manjunath.
出版者:	Cham :Springer International Publishing : : 2022.,
面頁冊數:	xiv, 103 p. :ill. (some col.), digital ;24 cm.
內容註:	1. Introduction -- 2. Literature review -- 3. Development and analysis of Multilingual Phone recognition system -- 4. Prediction of Multilingual Articulatory Features -- 5. Articulatory Features of Multilingual Phone recognition -- 6. Applications of Multilingual Phone recognition in Code-switched and Non-code-switched Scenarios -- 7. Summary and Conclusion.
Contained By:	Springer Nature eBook
標題:	Automatic speech recognition. -
電子資源:	https://doi.org/10.1007/978-3-030-80741-2
ISBN:	9783030807412

Multilingual phone recognition in Indian languages
K. E., Manjunath.

Multilingual phone recognition in Indian languages[electronic resource] /by Manjunath K. E. - Cham :Springer International Publishing :2022. - xiv, 103 p. :ill. (some col.), digital ;24 cm. - SpringerBriefs in speech technology,2191-7388. - SpringerBriefs in speech technology..

1. Introduction -- 2. Literature review -- 3. Development and analysis of Multilingual Phone recognition system -- 4. Prediction of Multilingual Articulatory Features -- 5. Articulatory Features of Multilingual Phone recognition -- 6. Applications of Multilingual Phone recognition in Code-switched and Non-code-switched Scenarios -- 7. Summary and Conclusion.

The book presents current research and developments in multilingual speech recognition. The author presents a Multilingual Phone Recognition System (Multi-PRS), developed using a common multilingual phone-set derived from the International Phonetic Alphabets (IPA) based transcription of six Indian languages - Kannada, Telugu, Bengali, Odia, Urdu, and Assamese. The author shows how the performance of Multi-PRS can be improved using tandem features. The book compares Monolingual Phone Recognition Systems (Mono-PRS) versus Multi-PRS and baseline versus tandem system. Methods are proposed to predict Articulatory Features (AFs) from spectral features using Deep Neural Networks (DNN) Multitask learning is explored to improve the prediction accuracy of AFs. Then, the AFs are explored to improve the performance of Multi-PRS using lattice rescoring method of combination and tandem method of combination. The author goes on to develop and evaluate the Language Identification followed by Monolingual phone recognition (LID-Mono) and common multilingual phone-set based multilingual phone recognition systems.

ISBN: 9783030807412

Standard No.: 10.1007/978-3-030-80741-2doiSubjects--Topical Terms:

753709
Automatic speech recognition.

LC Class. No.: TK7895.S65 / K4 2022

Dewey Class. No.: 006.454

Multilingual phone recognition in Indian languages
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505 0 $a 1. Introduction -- 2. Literature review -- 3. Development and analysis of Multilingual Phone recognition system -- 4. Prediction of Multilingual Articulatory Features -- 5. Articulatory Features of Multilingual Phone recognition -- 6. Applications of Multilingual Phone recognition in Code-switched and Non-code-switched Scenarios -- 7. Summary and Conclusion.
520 $a The book presents current research and developments in multilingual speech recognition. The author presents a Multilingual Phone Recognition System (Multi-PRS), developed using a common multilingual phone-set derived from the International Phonetic Alphabets (IPA) based transcription of six Indian languages - Kannada, Telugu, Bengali, Odia, Urdu, and Assamese. The author shows how the performance of Multi-PRS can be improved using tandem features. The book compares Monolingual Phone Recognition Systems (Mono-PRS) versus Multi-PRS and baseline versus tandem system. Methods are proposed to predict Articulatory Features (AFs) from spectral features using Deep Neural Networks (DNN) Multitask learning is explored to improve the prediction accuracy of AFs. Then, the AFs are explored to improve the performance of Multi-PRS using lattice rescoring method of combination and tandem method of combination. The author goes on to develop and evaluate the Language Identification followed by Monolingual phone recognition (LID-Mono) and common multilingual phone-set based multilingual phone recognition systems.
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