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020			_a9783030807412
024	7		_a10.1007/978-3-030-80741-2 _2doi
040			_aTR-AnTOB _beng _erda _cTR-AnTOB
041			_aeng
050		4	_aTK7895.S65
072		7	_aTJF _2bicssc
072		7	_aUYU _2bicssc
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072		7	_aTJF _2thema
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100	1		_aManjunath, K.E. _eauthor. _4aut _4http://id.loc.gov/vocabulary/relators/aut
245	1	0	_aMultilingual Phone Recognition in Indian Languages _h[electronic resource] / _cby K.E Manjunath.
250			_a1st ed. 2022.
264		1	_aCham : _bSpringer International Publishing : _bImprint: Springer, _c2022.
300			_a1 online resource
336			_atext _btxt _2rdacontent
337			_acomputer _bc _2rdamedia
338			_aonline resource _bcr _2rdacarrier
347			_atext file _bPDF _2rda
490	1		_aSpringerBriefs in Speech Technology, Studies in Speech Signal Processing, Natural Language Understanding, and Machine Learning, _x2191-7388
505	0		_a1. 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			_aThe 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.
650		0	_aSpeech processing systems.
650		0	_aSignal processing.
650		0	_aNatural language processing (Computer science).
650		0	_aComputational linguistics.
650	1	4	_aSpeech and Audio Processing.
650	2	4	_aNatural Language Processing (NLP).
650	2	4	_aComputational Linguistics.
653		0	_aAutomatic speech recognition
653		0	_aComputational linguistics -- India
710	2		_aSpringerLink (Online service)
830		0	_aSpringerBriefs in Speech Technology, Studies in Speech Signal Processing, Natural Language Understanding, and Machine Learning, _x2191-7388
856	4	0	_uhttps://doi.org/10.1007/978-3-030-80741-2 _3Springer eBooks _zOnline access link to the resource
942			_2lcc _cEBK